Explore exciting Machine Learning Engineer job opportunities. These roles involve developing algorithms and models that allow computers to learn from data. Machine learning engineers are in high demand across various sectors, including technology, finance, and healthcare, as companies seek to leverage data for better decision-making and automation. Key responsibilities include designing machine learning systems, conducting experiments, and implementing machine learning algorithms.What Jobs are available for Machine Learning Engineer in India?
Showing 2224 Machine Learning Engineer jobs in India
Machine Learning Engineer
Pune, Maharashtra
Emerson
Posted 3 days ago
Job Viewed
Job Description
**Job** **Summary:**
+ As a Machine Learning Engineer at Emerson, you will be responsible for developing, implementing, and optimizing machine learning models and systems. You will collaborate closely with data scientists, software engineers, and other collaborators to translate data insights into practical, scalable solutions
+ Design, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.
+ Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.
+ Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.
+ Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.
+ Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.
+ Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metrics
+ Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective
**In** **this** **Role,** **Your** **Responsibilities** **Will b** **e:**
+ Design, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.
+ Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.
+ Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.
+ Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.
+ Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.
+ Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metrics
+ Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective
**Who** **You** **Are:**
You quickly and decisively act in constantly evolving, unexpected situations. You adjust communication content and style to meet the needs of diverse partners. You always keep the end in sight; puts in extra effort to meet deadlines. You analyze multiple and diverse sources of information to define problems accurately before moving to solutions. You observe situational and group dynamics and select best-fit approach.
**For** **This** **Role,** **You** **Will** **Need:**
+ Bachelor's degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred.
+ More than 3 years of experience in machine learning engineering or a related role, with a strong track record of developing and deploying machine learning models.
+ Proficiency in programming languages such as Python or R. Experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch, scikit-learn).
+ Experience with Azure Cognitive services
+ Experience with data processing and manipulation tools and libraries (e.g., pandas, NumPy).
+ Strong analytical and problem-solving skills, with the ability to handle complex and large-scale data sets.
+ Experience with deploying machine learning models to production environments, including knowledge of containerization technologies (e.g., Docker or equivalent) and cloud platforms, Microsoft Azure is preferred
+ Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical collaborators
**Preferred** **Qualifications** **that** **Set** **You** **Apart:**
+ Prior experience in engineering domain would be nice to have
+ Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to have
+ Possession of relevant certification/s in data science from reputed universities specializing in AI.
+ Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
+ Understanding of standard processes in software development and methodologies.
**Requisition ID** :
Emerson is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, age, marital status, political affiliation, sexual orientation, gender identity, genetic information, disability or protected veteran status. We are committed to providing a workplace free of any discrimination or harassment.
+ As a Machine Learning Engineer at Emerson, you will be responsible for developing, implementing, and optimizing machine learning models and systems. You will collaborate closely with data scientists, software engineers, and other collaborators to translate data insights into practical, scalable solutions
+ Design, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.
+ Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.
+ Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.
+ Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.
+ Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.
+ Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metrics
+ Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective
**In** **this** **Role,** **Your** **Responsibilities** **Will b** **e:**
+ Design, build, and deploy machine learning models and algorithms to solve specific business problems. Optimize models for performance and scalability.
+ Work with large data sets to preprocess, clean, and transform data for use in machine learning models. Develop and maintain data pipelines.
+ Monitor and evaluate the performance of deployed models, making adjustments and improvements as needed to ensure accuracy and reliability.
+ Work with multi-functional teams such as data scientists, analysts, and product managers to understand requirements and deliver machine learning solutions that meet business needs.
+ Keep up with the latest research and trends in machine learning and artificial intelligence. Explore and implement new techniques and technologies to enhance model performance.
+ Document model development processes, code, and standard methodologies. Provide clear and comprehensive reports on model performance and metrics
+ Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint Retrospective
**Who** **You** **Are:**
You quickly and decisively act in constantly evolving, unexpected situations. You adjust communication content and style to meet the needs of diverse partners. You always keep the end in sight; puts in extra effort to meet deadlines. You analyze multiple and diverse sources of information to define problems accurately before moving to solutions. You observe situational and group dynamics and select best-fit approach.
**For** **This** **Role,** **You** **Will** **Need:**
+ Bachelor's degree in computer science, Data Science, Statistics, or a related field or a master's degree or higher is preferred.
+ More than 3 years of experience in machine learning engineering or a related role, with a strong track record of developing and deploying machine learning models.
+ Proficiency in programming languages such as Python or R. Experience with machine learning frameworks (e.g., Go, TensorFlow, PyTorch, scikit-learn).
+ Experience with Azure Cognitive services
+ Experience with data processing and manipulation tools and libraries (e.g., pandas, NumPy).
+ Strong analytical and problem-solving skills, with the ability to handle complex and large-scale data sets.
+ Experience with deploying machine learning models to production environments, including knowledge of containerization technologies (e.g., Docker or equivalent) and cloud platforms, Microsoft Azure is preferred
+ Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical collaborators
**Preferred** **Qualifications** **that** **Set** **You** **Apart:**
+ Prior experience in engineering domain would be nice to have
+ Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to have
+ Possession of relevant certification/s in data science from reputed universities specializing in AI.
+ Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
+ Understanding of standard processes in software development and methodologies.
**Requisition ID** :
Emerson is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, age, marital status, political affiliation, sexual orientation, gender identity, genetic information, disability or protected veteran status. We are committed to providing a workplace free of any discrimination or harassment.
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This advertiser has chosen not to accept applicants from your region.
0
Machine Learning Engineer
Pune, Maharashtra
Ensono
Posted 4 days ago
Job Viewed
Job Description
Machine Learning EngineerPune, IndiaJR
**Machine Learning Engineer**
At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things! We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.
We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose.
**HONESTY, RELIABILITY, COLLABORATION, CURIOSITY, PASSION**
At Ensono, we're transforming into a **software-first Managed Services Provider** , where AI/ML and automation move us from reactive firefighting to **predictive, zero-touch operations** . Our **Envision Operating System** is the platform that makes this shift possible-bringing together data, intelligence, and automation across mainframe, distributed, and cloud environments.
As a **Machine Learning Engineer (ML Engineer)** , you'll be the **builder who takes models from notebooks to production systems** . You'll work side-by-side with Data Scientists to translate their predictive insights into scalable, high-performance solutions that can run reliably at enterprise scale.
This is a role for **makers** -people who thrive at the intersection of code, models, and operations. You'll design APIs, deploy services, and ensure our AI capabilities integrate seamlessly with systems like **ServiceNow** , Snowflake, and Envision. Your work ensures that **incident predictions, anomaly detections, and optimization recommendations** don't just exist in theory-they power real-time operations, reduce downtime, and drive measurable business outcomes for our clients.
If you're the kind of engineer who loves making AI _actually work in production_ and want to be part of the team that's **rewiring managed services with intelligent automation** , this role is for you.
**What You Will Do:**
+ **Model Deployment** - Productionize machine learning models built by Data Scientists, ensuring they run reliably, securely, and at scale.
+ **API & Service Development** - Design APIs and services that expose model predictions to EnvisionOS, ServiceNow, and other enterprise systems.
+ **Performance Optimization** - Tune models for latency, throughput, and cost efficiency in real-time environments.
+ **Feature Pipeline Integration** - Collaborate with Data Engineers to ensure robust feature pipelines feed models consistently and with minimal drift.
+ **Automation & Scaling** - Use containers, orchestration, and CI/CD practices to automate deployment and monitoring of models.
+ **Cross-functional Collaboration** - Work with Ops, Data Science, and MLOps to ensure models deliver actionable, explainable outcomes that drive trust and adoption.
**We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply.**
**Required Skills & Experience**
+ Strong programming skills in **Python** (must-have) plus C, **C++, Java, Javascript** for performance-critical applications.
+ Experience with **ML frameworks** such as TensorFlow, PyTorch, or Scikit-learn.
+ Hands-on experience with **Docker, Kubernetes, or other container orchestration** tools.
+ Familiarity with **Snowflake** and data engineering workflows for integrating feature pipelines.
+ Experience deploying models in production and exposing them through **REST APIs, Flask, or Streamlit** .
+ Knowledge of SnowFlake is beneficial
+ Strong understanding of **model optimization, hyperparameter tuning, and inference performance** .
+ Experience working with **ServiceNow or IT operations datasets** is highly desirable.
**Mindset & Values**
+ **Get Stuff Done** - You take pride in moving models out of slides and into production.
+ **Builder at Heart** - You see APIs, services, and pipelines as products that should be reliable, elegant, and scalable.
+ **Impact-Oriented** - You measure success by **uptime improvements, cost savings, and real-world adoption** of AI-driven workflows.
+ **Collaborative Engineer** - You bridge the gap between Data Scientists and Ops teams, speaking both "ML" and "production."
+ **Continuous Improver** - Always looking for ways to make models faster, cheaper, and more accurate.
**Success Looks Like**
+ Models running in **production pipelines** , integrated with ServiceNow and EnvisionOS.
+ Predictions that **Ops teams trust and act on** , reducing downtime and improving MTTR.
+ Automated deployment workflows that keep models fresh, monitored, and reliable.
+ AI capabilities that scale across **mainframe, distributed, and cloud infrastructure** seamlessly.
**Why Ensono?**
Ensono is a place where we unleash Associates to Do Great Things - for our clients and for your career. This could mean achieving a professional goal, collaborating with your team on an innovative idea, learning a new skill, reaching a wellness milestone, or engaging in your community through volunteer programs. Whatever it means to you, we want Ensono to be the place where you can do great things.
We value flexibility and work-life balance. Positions that are not required to be onsite to support a client may offer the ability to work remotely or hybrid at an Ensono office location.
JR
**Machine Learning Engineer**
At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things! We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.
We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose.
**HONESTY, RELIABILITY, COLLABORATION, CURIOSITY, PASSION**
At Ensono, we're transforming into a **software-first Managed Services Provider** , where AI/ML and automation move us from reactive firefighting to **predictive, zero-touch operations** . Our **Envision Operating System** is the platform that makes this shift possible-bringing together data, intelligence, and automation across mainframe, distributed, and cloud environments.
As a **Machine Learning Engineer (ML Engineer)** , you'll be the **builder who takes models from notebooks to production systems** . You'll work side-by-side with Data Scientists to translate their predictive insights into scalable, high-performance solutions that can run reliably at enterprise scale.
This is a role for **makers** -people who thrive at the intersection of code, models, and operations. You'll design APIs, deploy services, and ensure our AI capabilities integrate seamlessly with systems like **ServiceNow** , Snowflake, and Envision. Your work ensures that **incident predictions, anomaly detections, and optimization recommendations** don't just exist in theory-they power real-time operations, reduce downtime, and drive measurable business outcomes for our clients.
If you're the kind of engineer who loves making AI _actually work in production_ and want to be part of the team that's **rewiring managed services with intelligent automation** , this role is for you.
**What You Will Do:**
+ **Model Deployment** - Productionize machine learning models built by Data Scientists, ensuring they run reliably, securely, and at scale.
+ **API & Service Development** - Design APIs and services that expose model predictions to EnvisionOS, ServiceNow, and other enterprise systems.
+ **Performance Optimization** - Tune models for latency, throughput, and cost efficiency in real-time environments.
+ **Feature Pipeline Integration** - Collaborate with Data Engineers to ensure robust feature pipelines feed models consistently and with minimal drift.
+ **Automation & Scaling** - Use containers, orchestration, and CI/CD practices to automate deployment and monitoring of models.
+ **Cross-functional Collaboration** - Work with Ops, Data Science, and MLOps to ensure models deliver actionable, explainable outcomes that drive trust and adoption.
**We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply.**
**Required Skills & Experience**
+ Strong programming skills in **Python** (must-have) plus C, **C++, Java, Javascript** for performance-critical applications.
+ Experience with **ML frameworks** such as TensorFlow, PyTorch, or Scikit-learn.
+ Hands-on experience with **Docker, Kubernetes, or other container orchestration** tools.
+ Familiarity with **Snowflake** and data engineering workflows for integrating feature pipelines.
+ Experience deploying models in production and exposing them through **REST APIs, Flask, or Streamlit** .
+ Knowledge of SnowFlake is beneficial
+ Strong understanding of **model optimization, hyperparameter tuning, and inference performance** .
+ Experience working with **ServiceNow or IT operations datasets** is highly desirable.
**Mindset & Values**
+ **Get Stuff Done** - You take pride in moving models out of slides and into production.
+ **Builder at Heart** - You see APIs, services, and pipelines as products that should be reliable, elegant, and scalable.
+ **Impact-Oriented** - You measure success by **uptime improvements, cost savings, and real-world adoption** of AI-driven workflows.
+ **Collaborative Engineer** - You bridge the gap between Data Scientists and Ops teams, speaking both "ML" and "production."
+ **Continuous Improver** - Always looking for ways to make models faster, cheaper, and more accurate.
**Success Looks Like**
+ Models running in **production pipelines** , integrated with ServiceNow and EnvisionOS.
+ Predictions that **Ops teams trust and act on** , reducing downtime and improving MTTR.
+ Automated deployment workflows that keep models fresh, monitored, and reliable.
+ AI capabilities that scale across **mainframe, distributed, and cloud infrastructure** seamlessly.
**Why Ensono?**
Ensono is a place where we unleash Associates to Do Great Things - for our clients and for your career. This could mean achieving a professional goal, collaborating with your team on an innovative idea, learning a new skill, reaching a wellness milestone, or engaging in your community through volunteer programs. Whatever it means to you, we want Ensono to be the place where you can do great things.
We value flexibility and work-life balance. Positions that are not required to be onsite to support a client may offer the ability to work remotely or hybrid at an Ensono office location.
JR
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This advertiser has chosen not to accept applicants from your region.
1
Machine Learning Engineer
Bengaluru, Karnataka
NetApp
Posted 2 days ago
Job Viewed
Job Description
**Job Summary**
NetApp is seeking an ML engineer to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively manage and govern their data estate and build cyber-resiliency while accelerating their digital transformation journey. To get to this vision, we will embark on an AI-first approach to build and deliver world-class suite of data services. As a key ML engineer in this initiative, the candidate will be responsible for independently deploying scalable AI/ML-based solutions, leveraging advancements in AI to solve real-world challenges in the domains of data protection and cyber-security. The candidate will possess deep expertise in using modern AI/ML systems to ship impactful products to production. This is going to be a challenging and a fun role in one of the most exciting roles in the industry today.
**Job Requirements**
+ Lead the development and deployment of AI/ML systems for Data protection with techniques from the realm of classical Machine learning, Generative AI and AI agents.
+ Develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, setting up automated evals, adopting latest and greatest inferencing platforms for rapid iterations.
+ Collaborate with data scientists and engineers to integrate AI into the broader products at NetApp. Effectively communicate complex technical artifacts to both technical and non-technical audiences.
+ Work with a great deal of autonomy and proactively bring open-source AI innovations into our research and experimentation roadmap. Ensure scalability, reliability, and performance of AI models in production environments.
+ Have a customer focus mindset and build AI/ML products that delight our customers.
+ Represent NetApp as an innovator in the machine learning community and promote the company's product capabilities in industry/academic conferences.
**Job Expectations**
+ The position is a Hybrid position, and the candidate is expected to work in NetApp Bangalore office at least two days a week.
**Required and Preferred Qualification**
+ Master's degree in computer science / applied mathematics / statistics / data science or equivalent experience.
+ 3+ years of experience in building MLOps pipelines, CI/CD pipelines, and ML systems lifecycle management.
+ Strong knowledge of optimizing and shipping machine learning and deep learning models to production.
+ Proficiency in Python, SQL and at least one cloud platform (AWS, Azure or GCP).
+ Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders of an organization
**Preferred Qualification**
+ 1+ years of experience in data engineering, including building and optimizing data pipelines and architectures.
+ Solid understanding of data science fundamentals and model evaluations, including supervised and unsupervised machine learning algorithms (both machine learning and deep learning).
+ Good understanding of cyber-security and data protection frameworks.
+ Experience of representing your work or company at AI/ML conferences.
+ Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements.
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
**Equal Opportunity Employer:**
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, and any protected classification.
**Why NetApp?**
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
We enable a healthy work-life balance. Our volunteer time off program is best in class, offering employees 40 hours of paid time off each year to volunteer with their favourite organizations. We provide comprehensive benefits, including health care, life and accident plans, emotional support resources for you and your family, legal services, and financial savings programs to help you plan for your future. We support professional and personal growth through educational assistance and provide access to various discounts and perks to enhance your overall quality of life.
If you want to help us build knowledge and solve big problems, let's talk.
NetApp is seeking an ML engineer to join the Data Services organization. The overarching vision of this organization is to empower organizations to effectively manage and govern their data estate and build cyber-resiliency while accelerating their digital transformation journey. To get to this vision, we will embark on an AI-first approach to build and deliver world-class suite of data services. As a key ML engineer in this initiative, the candidate will be responsible for independently deploying scalable AI/ML-based solutions, leveraging advancements in AI to solve real-world challenges in the domains of data protection and cyber-security. The candidate will possess deep expertise in using modern AI/ML systems to ship impactful products to production. This is going to be a challenging and a fun role in one of the most exciting roles in the industry today.
**Job Requirements**
+ Lead the development and deployment of AI/ML systems for Data protection with techniques from the realm of classical Machine learning, Generative AI and AI agents.
+ Develop scalable data pipelines for various AI/ML-driven solutions from building curated data pipelines, setting up automated evals, adopting latest and greatest inferencing platforms for rapid iterations.
+ Collaborate with data scientists and engineers to integrate AI into the broader products at NetApp. Effectively communicate complex technical artifacts to both technical and non-technical audiences.
+ Work with a great deal of autonomy and proactively bring open-source AI innovations into our research and experimentation roadmap. Ensure scalability, reliability, and performance of AI models in production environments.
+ Have a customer focus mindset and build AI/ML products that delight our customers.
+ Represent NetApp as an innovator in the machine learning community and promote the company's product capabilities in industry/academic conferences.
**Job Expectations**
+ The position is a Hybrid position, and the candidate is expected to work in NetApp Bangalore office at least two days a week.
**Required and Preferred Qualification**
+ Master's degree in computer science / applied mathematics / statistics / data science or equivalent experience.
+ 3+ years of experience in building MLOps pipelines, CI/CD pipelines, and ML systems lifecycle management.
+ Strong knowledge of optimizing and shipping machine learning and deep learning models to production.
+ Proficiency in Python, SQL and at least one cloud platform (AWS, Azure or GCP).
+ Excellent communication and collaboration skills, with demonstrated ability to work effectively with cross-functional teams and stakeholders of an organization
**Preferred Qualification**
+ 1+ years of experience in data engineering, including building and optimizing data pipelines and architectures.
+ Solid understanding of data science fundamentals and model evaluations, including supervised and unsupervised machine learning algorithms (both machine learning and deep learning).
+ Good understanding of cyber-security and data protection frameworks.
+ Experience of representing your work or company at AI/ML conferences.
+ Active GitHub profile showcasing relevant open-source AI/ML projects or Kaggle achievements.
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
**Equal Opportunity Employer:**
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, and any protected classification.
**Why NetApp?**
We are all about helping customers turn challenges into business opportunity. It starts with bringing new thinking to age-old problems, like how to use data most effectively to run better - but also to innovate. We tailor our approach to the customer's unique needs with a combination of fresh thinking and proven approaches.
We enable a healthy work-life balance. Our volunteer time off program is best in class, offering employees 40 hours of paid time off each year to volunteer with their favourite organizations. We provide comprehensive benefits, including health care, life and accident plans, emotional support resources for you and your family, legal services, and financial savings programs to help you plan for your future. We support professional and personal growth through educational assistance and provide access to various discounts and perks to enhance your overall quality of life.
If you want to help us build knowledge and solve big problems, let's talk.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
2
Machine Learning Engineer
Hyderabad, Andhra Pradesh
Amgen
Posted 4 days ago
Job Viewed
Job Description
**Join Amgen's Mission of Serving Patients**
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Machine Learning Engineer
**What you will do**
Let's do this. Let's change the world. In this vital role as a Machine Learning Engineer, you will contribute to the development and maintenance of our GEN AI web applications across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations. This role is ideal for recent graduates or early-career professionals looking to gain hands-on experience in software development.
**Roles & Responsibilities:**
+ Implement, and optimize LLM-powered models for document processing, data extraction, and application Insights
+ Develop and optimize retrieval-augmented generation (RAG) pipelines to improve query processing and information retrieval
+ Work with large-scale structured and unstructured data to ensure efficient indexing, retrieval, and contextual relevance
+ Collaborate with the design and product teams to understand user needs and translate them into technical requirements.
+ Write clean, efficient, and well-tested code.
+ Participate in code reviews and provide constructive feedback.
+ Maintain system uptime and optimal performance
+ Learn and adapt to new technologies and industry trends like Prompt Engineering, AI tools and Retrieval-augmented generation (RAG) frameworks
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients. The (vital attribute) professional we seek is a (type of person) with these qualifications.
**Basic Qualifications:**
Master's degree / Bachelor's degree and 5 to 9 years
**Preferred Qualifications:**
**Functional Skills:**
+ Proficiency in Python and data manipulation libraries (Pandas, NumPy, etc.)
+ Familiarity with machine learning workflows and common ML libraries (scikit-learn, PyTorch, TensorFlow)
+ Working knowledge of cloud environments (AWS, Azure, or Google Cloud Platform)
+ Experience with popular large language models like OPEN AI
+ Experience with language models and frameworks like Langchain or llamaIndex
+ Proficiency with prompt engineering, model fine tuning
+ Familiarity with DevOps CICD build and deployment pipeline
+ Experience with design patterns, data structures, test-driven development.
**Professional Certifications:**
+ AWS, Data Science Certifications(preferred)
**Soft Skills:**
+ Excellent analytical and troubleshooting skills.
+ Strong verbal and written communication skills.
+ Ability to work effectively with global, virtual teams.
+ High degree of initiative and self-motivation.
+ Ability to manage multiple priorities successfully.
+ Team-oriented, with a focus on achieving team goals.
+ Strong presentation and public speaking skills.
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Machine Learning Engineer
**What you will do**
Let's do this. Let's change the world. In this vital role as a Machine Learning Engineer, you will contribute to the development and maintenance of our GEN AI web applications across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations. This role is ideal for recent graduates or early-career professionals looking to gain hands-on experience in software development.
**Roles & Responsibilities:**
+ Implement, and optimize LLM-powered models for document processing, data extraction, and application Insights
+ Develop and optimize retrieval-augmented generation (RAG) pipelines to improve query processing and information retrieval
+ Work with large-scale structured and unstructured data to ensure efficient indexing, retrieval, and contextual relevance
+ Collaborate with the design and product teams to understand user needs and translate them into technical requirements.
+ Write clean, efficient, and well-tested code.
+ Participate in code reviews and provide constructive feedback.
+ Maintain system uptime and optimal performance
+ Learn and adapt to new technologies and industry trends like Prompt Engineering, AI tools and Retrieval-augmented generation (RAG) frameworks
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients. The (vital attribute) professional we seek is a (type of person) with these qualifications.
**Basic Qualifications:**
Master's degree / Bachelor's degree and 5 to 9 years
**Preferred Qualifications:**
**Functional Skills:**
+ Proficiency in Python and data manipulation libraries (Pandas, NumPy, etc.)
+ Familiarity with machine learning workflows and common ML libraries (scikit-learn, PyTorch, TensorFlow)
+ Working knowledge of cloud environments (AWS, Azure, or Google Cloud Platform)
+ Experience with popular large language models like OPEN AI
+ Experience with language models and frameworks like Langchain or llamaIndex
+ Proficiency with prompt engineering, model fine tuning
+ Familiarity with DevOps CICD build and deployment pipeline
+ Experience with design patterns, data structures, test-driven development.
**Professional Certifications:**
+ AWS, Data Science Certifications(preferred)
**Soft Skills:**
+ Excellent analytical and troubleshooting skills.
+ Strong verbal and written communication skills.
+ Ability to work effectively with global, virtual teams.
+ High degree of initiative and self-motivation.
+ Ability to manage multiple priorities successfully.
+ Team-oriented, with a focus on achieving team goals.
+ Strong presentation and public speaking skills.
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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3
Machine Learning Engineer
Hyderabad, Andhra Pradesh
Amgen
Posted 4 days ago
Job Viewed
Job Description
**Join Amgen's Mission of Serving Patients**
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
**Machine Learning Engineer**
**What you will do**
Let's do this. Let's change the world. In this vital role We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.
**Roles & Responsibilities:**
+ Collaborate with data scientists to develop, train, and evaluate machine learning models.
+ Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
+ Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
+ Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.
+ Develop and implement monitoring systems to track model performance and identify issues.
+ Conduct A/B testing and experimentation to optimize model performance.
+ Work closely with data scientists, engineers, and product teams to deliver ML solutions.
+ Stay updated with the latest trends and advancements
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients.
**Basic Qualifications:**
+ Master's degree / Bachelor's degree and 5 to 9 years (Job Code's Discipline and/or Sub-Discipline)
**Functional Skills:**
**Must-Have Skills:**
+ Solid foundation in machine learning algorithms and techniques
+ Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
+ Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
+ Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and interpersonal skills
**Good-to-Have Skills:**
+ Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
+ Experience with data engineering and pipeline development
+ Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
+ Knowledge of NLP techniques for text analysis and sentiment analysis
+ Experience in analyzing time-series data for forecasting and trend analysis
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.
Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
**Machine Learning Engineer**
**What you will do**
Let's do this. Let's change the world. In this vital role We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines.
**Roles & Responsibilities:**
+ Collaborate with data scientists to develop, train, and evaluate machine learning models.
+ Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.
+ Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment.
+ Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency.
+ Develop and implement monitoring systems to track model performance and identify issues.
+ Conduct A/B testing and experimentation to optimize model performance.
+ Work closely with data scientists, engineers, and product teams to deliver ML solutions.
+ Stay updated with the latest trends and advancements
**What we expect of you**
We are all different, yet we all use our unique contributions to serve patients.
**Basic Qualifications:**
+ Master's degree / Bachelor's degree and 5 to 9 years (Job Code's Discipline and/or Sub-Discipline)
**Functional Skills:**
**Must-Have Skills:**
+ Solid foundation in machine learning algorithms and techniques
+ Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
+ Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
+ Outstanding analytical and problem-solving skills; Ability to learn quickly; Good communication and interpersonal skills
**Good-to-Have Skills:**
+ Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
+ Experience with data engineering and pipeline development
+ Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
+ Knowledge of NLP techniques for text analysis and sentiment analysis
+ Experience in analyzing time-series data for forecasting and trend analysis
**What you can expect of us**
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.
In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards.
**Apply now and make a lasting impact with the Amgen team.**
**careers.amgen.com**
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
4
Machine Learning Engineer
BayOne Solutions
Posted 6 days ago
Job Viewed
Job Description
Responsibilities:
Machine Learning Development & Implementation (40%)
- Design and implement end-to-end ML pipelines for recommendation systems, search ranking, and classification problems
- Build and optimize traditional ML models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks
- Develop time series forecasting models and ranking algorithms for complex business applications
- Implement feature engineering pipelines that handle real-world data noise and edge cases
- Create robust data preprocessing and validation systems that ensure model reliability in production
Production ML Systems & Deployment (25%)
- Deploy ML models using Docker containerization and REST API frameworks (Flask/FastAPl)
- Implement model serving solutions on Azure Container Instances with proper monitoring and
alerting
- Build MLOps pipelines using MLflow for experiment tracking and model registry management
- Design scalable data workflows using Apache Airflow and Azure Data Factory for ETL operations
- Establish model versioning, rollback strategies, and performance monitoring in production environments
Technical Leadership & Collaboration (20%)
- Serve as a technical sounding board for AI team members on ML architecture and approach decisions
- Mentor team members on best practices for production ML system design and implementation
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders
- Collaborate across AI, web development, and system architecture teams toensure seamless integration
- Guide strategic decisions on when to use traditional ML versus generative AI approaches
Strategic ML Decision Making (15%)
- Evaluate problems to determine optimal solutions: classical ML, GenAI, or simpler analytical methods
- Integrate generative AI tools effectively into workflows without over-relying on them
- Design ML systems that integrate seamlessly with existing web application architectures
- Provide technical guidance onmodel selection, evaluation metrics, and performance optimization
- Stay current with ML best practices while maintaining focus on practical, business-driven solutions
Required Qualifications
Education & Experience
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field
- 4+ years of hands-on experience building and deploying machine learning systems in production
- Proven experience working in non-technical business domains (healthcare, finance, retail, HR, etc.)
- Track record of mentoring technical team members and leading collaborative projects
Core Technical Skills
- Programming Excellence: Expert-level Python proficiency with focus on clean, maintainable, production-ready code
- Traditional ML Expertise: Deep understanding of classification, regression, ranking, and recommendation algorithms
- Production ML: Experience with MLOps practices, model deployment, monitoring, and lifecycle management
- Data Engineering: Proficiency with data pipeline development, ETL processes, and handling messy real-world datasets
- Cloud Platforms: Hands-on experience with Azure ML Studio, Azure Container Instances, and Azure Data Factory
Specialized Experience:
- Experience building recommendation engines, search ranking systems, or time series forecasting models
- Background in A/B testing methodologies and measuring business impact of ML initiatives
- Knowledge of feature stores, model registry systems, and ML experiment tracking
- Understanding of model interpretability, bias detection, and fairness in ML systems
- Experience with both structured and unstructured data processing at scale
- Experience with deep learning frameworks (TensorFlow, PyTorch) for appropriate use cases
Preferred Qualifications
- Knowledge of natural language processing techniques and text classification systems
- Background in building ML systems for talent acquisition, recruiting, or HR technology
- Experience with real-time ML inference and low-latency model serving
- Understanding of distributed computing and large-scale data processing
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5
Machine Learning Engineer
Mumbai, Maharashtra
Tata Consultancy Services
Posted 6 days ago
Job Viewed
Job Description
Role-Machine Learning Engineer
Skills required- Python, AI, ML
Location- Bangalore, Mumbai
Year of experience - 6 to 10 years
Job description:
- Machine Learning Engineers will work on all AI and ML technologies - machine learning, knowledge graphs, cognitive etc. – to Design, develop and implement solutions.
- Experience with Machine Learning algorithms.
- Expertise in Python
- Deep understanding of data structures and algorithms.
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6
Machine Learning Engineer
Hyderabad, Andhra Pradesh
Canterr, Inc.
Posted 8 days ago
Job Viewed
Job Description
Role: Staff Machine Learning Engineer - Generative AI - L3
Location: Hyderabad / Hybrid
Notice: Immediate
Experience: 7+ years
What You’ll Do
- Lead with vision —set the technical direction for our generative AI team, establish best practices, and inspire high-impact innovation.
- Drive strategy —Help shape the AI roadmap, identifying the most valuable opportunities to apply generative AI across Xometry’s marketplace.
- Build cutting-edge models —Develop and deploy large language and generative models for multimodal document processing and structured data extraction.
- Innovate across modalities —Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions.
- Engineer at scale —Create data pipelines and training workflows that can handle massive, complex datasets.
- Deploy in the cloud —Use AWS and other platforms to train, optimize, and deploy models into production at scale.
- Collaborate widely —work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows.
- Mentor and grow —Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team.
- Stay ahead —keep up with the latest generative AI and deep learning research, and bring fresh ideas into production.
What We’re Looking For
- A bachelor’s degree is required; an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is a big plus.
- 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision.
- Strong track record working with large-scale language and vision models (transformers, GPT, and VLMs).
- Hands-on experience with multimodal data (text, images, 3D).
- Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy).
- Solid grounding in probability, statistics, and optimization for generative modeling.
- Experience deploying ML and AI models using cloud microservice architecture (AWS preferred).
- Strong software engineering skills, including object-oriented programming, testing, version control, CI/CD best practices, and IaC (Terraform preferred).
- A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders.
- Background in manufacturing, supply chain, or related industries is a plus—but curiosity and drive matter more.
Note: Associates from product-based organizations are preferred.
Associates should complete the interview process within in 2 or 3 days after processing
PF Service History is mandatory
Irrelevant Profiles will not be considered; please go through the Job description completely before applying
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7
Machine Learning Engineer
Aakaar AI
Posted 1 day ago
Job Viewed
Job Description
About Us
We're a small but ambitious startup revolutionizing the e-commerce landscape with cutting-edge AI solutions. Our mission is to empower sellers with the tools and insights they need to thrive in the competitive online marketplace.
We’re building a suite of AI-powered products and intelligent AI agents designed to streamline advertising, automate research, optimize listings, boost sales, and drive growth for businesses of all sizes.
The Role: Senior Machine Learning Engineer (AI/ML & LLMs – E-Commerce Ads)
We’re looking for a Senior Machine Learning Engineer to join our team and play a key role in developing the intelligence behind our AI-driven e-commerce platform.
In this role, you’ll be responsible for designing, building, training, optimizing, and deploying machine learning and LLM-based models that power ad targeting , recommendation systems , personalization engines , performance prediction , and autonomous AI agents .
You’ll own end-to-end ML pipelines — from data ingestion and feature engineering to model development , evaluation , and deployment — while also working hands-on with large language models to build intelligent workflows, tools, and automation.
Responsibilities
- ML & AI Model Development: Build, train, evaluate, and optimize ML models for ad performance prediction, personalization, targeting, and campaign optimization.
- Experiment with classical ML and modern deep learning architectures to maximize performance.
- LLM Development & Integration: Fine-tune, prompt-engineer, or build applications using large language models (e.g., OpenAI GPT-4, Claude, LLaMA).
- Build intelligent agent workflows using LLMs for research automation, ad copy generation, optimization strategies, and seller assistance.
- Integrate LLMs with internal data pipelines and APIs to deliver context-aware insights.
- Data Pipelines & Feature Engineering: Design and implement scalable data pipelines for training and inference.
- Process structured and unstructured e-commerce ad data for ML and LLM applications.
- Model Deployment & Infrastructure: Deploy ML and LLM models to production using containerization, inference APIs, or orchestration frameworks.
- Collaborate with backend teams to ensure seamless interaction between AI systems and product interfaces.
- Experimentation & Evaluation: Design and run experiments (e.g., A/B testing) to evaluate and iterate on models.
- Monitor model performance post-deployment and implement retraining or optimization strategies.
- Architecture & Scalability: Contribute to the design of AI infrastructure supporting rapid experimentation and reliable deployment at scale.
- Research & Innovation: Stay current on the latest advancements in ML, LLMs, and agentic AI systems.
- Propose and prototype new capabilities to strengthen our product’s intelligence.
Qualifications
- Experience: 3+ years of professional experience as a Machine Learning Engineer or similar role.
- Proven experience building and deploying ML models and/or LLM-based solutions into production.
- Technical Skills: Proficiency in Python/Javascript and ML/AI frameworks like PyTorch, TensorFlow, or scikit-learn.
- Strong understanding of ML algorithms, model evaluation, feature engineering, and MLOps best practices.
- Experience working with and deploying LLMs (e.g., OpenAI GPT-4, Claude, LLaMA, or similar).
- Familiarity with prompt engineering, fine-tuning, RAG (retrieval-augmented generation), and agent frameworks.
- Experience with cloud platforms like Google Cloud Platform, Amazon Web Services, or Microsoft Azure.
- Experience with containerization and model serving (e.g., Docker, Kubernetes, TensorFlow Serving, FastAPI).
- Applied AI Experience: Strong background in supervised/unsupervised learning, predictive modeling, and experimentation.
- Experience with recommender systems, ad optimization models, or marketing intelligence.
- Familiarity with LLM integrations in production systems is a big plus.
- Soft Skills: Strong problem-solving abilities and ownership mindset.
- Excellent communication and collaboration skills.
- Comfortable in a fast-moving startup environment.
Bonus Points
- Experience applying LLMs to real-world product use cases in e-commerce or marketing.
- Knowledge of agentic AI architectures and multi-model orchestration.
- Experience contributing to open-source ML/LLM projects.
- Familiarity with backend/frontend systems to integrate AI into customer experiences.
- Domain experience with e-commerce platforms (e.g., Amazon Seller Central).
Why Join Us
- Build AI that directly impacts thousands of e-commerce businesses.
- Work on both ML and LLM innovation at the frontier of applied AI.
- Own your work end-to-end in a lean, ambitious team.
- Flexible work culture, high autonomy, and the chance to shape the future of our platform.
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8
Machine Learning Engineer
Pune, Maharashtra
TerraGiG
Posted 8 days ago
Job Viewed
Job Description
We are looking for ML Ops Engineer
Experience: 6+ Years
Location: Pune, Mumbai, Bangalore, Hyderabad, Gurugram, Chandigarh
Shift: Full-time ( Noon timing- 3:30 pm - 12:30 am)
Required Skills:
MLOps, Python FastAPI, ML Models, DevOps
Responsibilities:
- Build scalable apps using Python & FastAPI with database integration.
- Review codebase and optimize existing ML models .
- Deploy & integrate Hugging Face ML models .
- Implement MLOps pipelines (training, deployment, monitoring).
- Apply DevOps practices (Docker, Kubernetes, CI/CD, cloud).
Requirements:
- Strong in Core Python, FastAPI/Flask/Django .
- Experience in database integration (SQL/NoSQL).
- Knowledge of ML lifecycle, MLOps & Hugging Face models .
- DevOps/MLOps tools: Docker, Kubernetes, MLflow, CI/CD .
- Cloud (AWS/GCP/Azure) exposure preferred.
Interested candidates please share your resume to along with the following details:
Total Exp:
Relevant Exp as MLops Engineer:
Notice Period and LWD:
Current Location:
How many years of exp in Python:
How many years of exp in FastAPI:
How many years of exp in ML Models:
How many years of exp in Devops:
How many years of exp in SQL/NoSQL:
Current CTC:
Expected CTC:
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9