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.6,676 Machine Learning Engineer jobs in India
Machine Learning Engineer/ Senior Machine Learning Engineer
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Job Description
Who We are:
We are a team of Ecommerce enthusiasts, passionate about using technology to simplify Digital Commerce and Payments for brands across the globe. Paxcom a leading Digital Solution Provider is a part of Paymentus now, a leading electronic bill payment provider. PaymentUs leads the North American marketplace in electronic bill payment solutions and have recently signed a partnership with Paypal, Alexa and Walmart.
For more details, please visit &
Job Position : AI/ML Engineering
Job Location: Gurgaon (Work From Office)
Job Summary
We're looking for a passionate and hands-on Machine Learning Engineer to join our fast-paced E-commerce team. You'll work on cutting-edge projects involving Large Language Models (LLMs), full MLOps lifecycle, and scalable deployment of AI solutions.
Key Responsibilities
Design, build, and deploy end-to-end machine learning solutions for production.
Fine-tune and integrate Large Language Models (LLMs), including experience with RAG, APIs from OpenAI, Google, Anthropic, etc.
Implement and manage robust MLOps workflows using tools like Docker, CI/CD pipelines, and cloud ML services such as SageMaker or Vertex AI.
Work with structured and unstructured data, leveraging both SQL and NoSQL databases.
Collaborate with cross-functional teams to translate business requirements into technical solutions.
Continuously explore and experiment with new models (e.g., Llama 3, Mistral, open-source LLMs) and frameworks as soon as they're released.
Essential Skills:Programming: Expert in Python with strong experience in Pandas, NumPy, and data processing.
ML Frameworks: Deep hands-on experience with PyTorch, TensorFlow, and Scikit-learn.
LLMs: Proven experience with fine-tuning, RAG, and working with LLM APIs from providers like OpenAI, Google, and Anthropic.
MLOps & Cloud: Solid experience across the MLOps lifecycle with tools like Docker and CI/CD pipelines. Proficiency in at least one major cloud platform (AWS, GCP, or Azure) and their ML services.
Data Handling: Proficient in working with SQL/NoSQL databases and scalable data storage systems.
Tech Curiosity: Actively stays up to date with the latest in ML/AI – whether that's testing new LLMs, trying out novel frameworks, or exploring new techniques.
Desirable Traits:Product Thinking: You think beyond models—you focus on building products that deliver value.
Problem Solving: Comfortable navigating ambiguous challenges and developing practical solutions.
Communication: Able to explain technical concepts clearly to both technical and non-technical stakeholders.
Team Collaboration: Thrive in agile environments, enjoy knowledge sharing, and work well with diverse teams.
What we expect from you?
You have the ability to work in a fast-paced environment adapting to changing priorities
You are focused and detail oriented but know when to seek help from others
You have excellent written and verbal communication skills to articulate problems and solutions to both technical and non-technical audiences
You possess superior troubleshooting and analytical skills to determine the root cause of issues
You strive to identify areas of improvement and work proactively to prevent issues from occurring
You are a self-starter with an appreciation for tackling technical challenges of varying complexity
You are diligent when making decisions and can easily justify your actions.
Why Join us?
You hate micromanagement and freedom to work is important to you
Enjoy flexible and relaxed work environment
Work life Balance is important to you
Enjoy Motivating Working Conditions
A friendly, Supportive, Professional and achievement-oriented management team
Competitive remuneration
An opportunity to learn new things every day and work on latest technologies
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
**Team Overview:**
Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.
**What you get to do in this role:**
+ Design, develop, and evaluate end-to-end machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.
+ Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
+ Conduct cutting-edge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.
+ Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.
+ Fine-tune and deploy large-scale models, incorporating prompt engineering, few-shot learning, and retrieval-augmented techniques.
+ Collaborate cross-functionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to open-source or peer-reviewed ML/AI research.
+ Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.
+ Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.
+ Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.
**Key qualifications:**
1. Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
2. Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
3. **2+ years of experience in machine learning, deep learning, LLM, with a track record of applied research or experimentation.**
4. Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
5. Hands-on experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
6. Proven experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.
7. Familiarity with data-centric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.
8. Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.
9. Practical experience deploying models using inference platforms like Triton, ONNX in production environments.
10. Experience working with MLOps stacks: CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
11. Excellent communication skills with the ability to explain complex ML ideas to non-technical stakeholders and contribute to scientific documentation.
**Work Personas**
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here ( . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
**Equal Opportunity Employer**
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
**Accommodations**
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact for assistance.
**Export Control Regulations**
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
**Team Overview:**
Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.
**What you get to do in this role:**
+ Design, develop, and evaluate end-to-end machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.
+ Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
+ Conduct cutting-edge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.
+ Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.
+ Fine-tune and deploy large-scale models, incorporating prompt engineering, few-shot learning, and retrieval-augmented techniques.
+ Collaborate cross-functionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to open-source or peer-reviewed ML/AI research.
+ Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.
+ Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.
+ Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.
**Key qualifications:**
1. Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
2. Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
3. **2+ years of experience in machine learning, deep learning, LLM's with a track record of applied research or experimentation.**
4. Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
5. Hands-on experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
6. Proven experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.
7. Familiarity with data-centric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.
8. Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.
9. Practical experience deploying models using inference platforms like Triton, ONNX in production environments.
10. Experience working with MLOps stacks: CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
11. Excellent communication skills with the ability to explain complex ML ideas to non-technical stakeholders and contribute to scientific documentation.
**Work Personas**
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here ( . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
**Equal Opportunity Employer**
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
**Accommodations**
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact for assistance.
**Export Control Regulations**
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted 5 days ago
Job Viewed
Job Description
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.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
TE-4 Years and above
Location- Bangalore/Chennai/Hyderabad
NP- 15-30 Days max
JOB DESCRIPTION
Join our fast‑growing team to build a unified platform for data analytics, machine learning, and generative AI. You’ll integrate the AI/ML toolkit, real‑time streaming into a backed feature store, and dashboards—turning raw events into reliable features, insights, and user‑facing analytics at scale.
What you’ll do
- Design and build streaming data pipelines (exactly‑once or effectively‑once) from event sources into low‑latency feature serving and NRT and OLAP queries.
- Develop an AI/ML toolkit: reusable libraries, SDKs, and CLIs for data ingestion, feature engineering, model training, evaluation, and deployment.
- Stand up and optimize a production feature store (schemas, SCD handling, point‑in‑time correctness, TTL/compaction, backfills).
- Expose features and analytics via well‑designed APIs/Services; integrate with model serving and retrieval for ML/GenAI use cases.
- Build and operationalize Superset dashboards for monitoring data quality, pipeline health, feature drift, model performance, and business KPIs.
- Implement governance and reliability: data contracts, schema evolution, lineage, observability, alerting, and cost controls.
- Partner with UI/UX, data science, and backend teams to ship end‑to‑end workflows from data capture to real‑time inference and decisioning.
- Drive performance: benchmark and tune distributed DB (partitions, indexes, compression, merge settings), streaming frameworks, and query patterns.
- Automate with CI/CD, infrastructure‑as‑code, and reproducible environments for quick, safe releases.
Tech you may use
Languages: Python, Java/Scala, SQL
Streaming/Compute: Kafka (or Pulsar), Spark, Flink, Beam
Storage/OLAP: ClickHouse (primary), object storage (S3/GCS), Parquet/Iceberg/Delta
Orchestration/Workflow: Airflow, dbt (for transformations), Makefiles/Poetry/pipenv
ML/MLOps: MLflow/Weights & Biases, KServe/Seldon, Feast/custom feature store patterns, vector stores (optional)
Dashboards/BI: Superset (plugins, theming), Grafana for ops
Platform: Kubernetes, Docker, Terraform, GitHub Actions/GitLab CI, Prometheus/OpenTelemetry
Cloud: AWS/GCP/Azure
What we’re looking for
- 4+ years building production data/ML or streaming systems with high TPS and large data volumes.
- Strong coding skills in Python and one of Java/Scala; solid SQL and data modeling.
- Hands‑on experience with Kafka (or similar), Spark/Flink, and OLAP stores—ideally ClickHouse.
- GenAI pipelines: retrieval‑augmented generation (RAG), embeddings, prompt/tooling workflows, model evaluation at scale.
- Proven experience designing feature pipelines with point‑in‑time correctness and backfills; understanding of online/offline consistency.
- Experience instrumenting Superset dashboards tied to ClickHouse for operational and product analytics.
- Fluency with CI/CD, containerization, Kubernetes, and infrastructure‑as‑code.
- Solid grasp of distributed systems and architecture fundamentals: partitioning, consistency, idempotency, retries, batching vs. streaming, and cost/perf trade‑offs.
- Excellent collaboration skills; ability to work cross‑functionally with DS/ML, product, and UI/UX.
- Ability to pass a CodeSignal prescreen coding test.
Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.
To learn more about Grid Dynamics, please visit . Follow us on Facebook , Twitter , and LinkedIn .
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Machine Learning Engineer
Posted today
Job Viewed
Job Description
Position: Machine Learning Engineer
Location: Remote (India).
Type: Full-time (with BayOne).
Work Time : IST (02.00 PM to 10.00 PM IST).
Key Skills & Experience:
Proficiency with ML frameworks (TensorFlow, PyTorch)
NLP and Large Language Models (LLMs) experience
Strong understanding of generative models and applications
Programming skills in Python, Go, or Java
API development and model integration expertise
Familiarity with Docker, Kubernetes Knowledge of CI/CD pipelines, databases(MongoDB), data lakes, or real-time data processing tools
BayOne is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any federal, state, or local protected class. This job posting represents the general duties and requirements necessary to perform this position and is not an exhaustive statement of all responsibilities, duties, and skills required. Management reserves the right to revise or alter this job description.
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Machine Learning Engineer
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Job Description
Location: Noida / Indore / Bengaluru / Hyderabad
Experience: 6–12 Years (Senior role)
Education: BE / B.Tech / M.Tech / MCA / M.Com
Job Summary:
We are seeking an experienced Machine Learning Engineer with a strong background in designing, developing, and scaling chatbot and conversational AI solutions on AWS. In this role, you will collaborate closely with product, engineering, and data teams to build intelligent, secure, and scalable conversational systems that seamlessly integrate with enterprise platforms.
Key Responsibilities
- Architect, develop, and deploy chatbot solutions using AWS services such as Lambda, API Gateway, DynamoDB, and S3.
- Design and implement NLP pipelines, dialogue flows, and robust fallback/error-handling strategies.
- Integrate chatbot systems with enterprise tools and applications (e.g., CRM, HRMS, internal platforms).
- Ensure high availability, performance optimization, and cost efficiency of chatbot workloads on AWS.
- Implement monitoring, logging, and analytics for tracking and improving chatbot performance.
- Collaborate with cross-functional teams including product managers, UX designers, and data scientists to enhance conversational user experiences.
- Apply cloud security best practices to safeguard data and access within the chatbot ecosystem.
Required Skills
- Extensive hands-on experience with AWS services: Lambda, S3, DynamoDB, API Gateway, CloudWatch, IAM, etc.
- Strong programming skills in at least one language: Python, Node.js, or Java.
- Solid understanding of Machine Learning and Artificial Intelligence, with a focus on NLP.
- Experience with conversational AI frameworks such as Rasa, Dialogflow, or similar.
- Expertise in integrating RESTful APIs, GraphQL, and Webhooks.
- Familiarity with CI/CD processes and tools (e.g., CodePipeline, GitHub Actions, Jenkins).
- Knowledge of cloud security, IAM policies, and best practices.
- Experience developing APIs using frameworks like FastAPI or Flask.
- Understanding of AI Agents and their application in dynamic conversational systems.
Preferred/Bonus Skills
- Exposure to Generative AI tools and platforms (e.g., Amazon Bedrock, OpenAI APIs, Anthropic Claude).
- Experience with front-end integrations for chatbots (React, Angular, mobile apps, or messaging platforms like WhatsApp, Slack, Teams).
- Familiarity with MLOps practices and deploying custom NLP models in production.
- Knowledge of chatbot analytics and performance tools (e.g., Amazon Kendra, QuickSight, or third-party platforms).
For Quick Response- Interested Candidates can directly share their resume along with the details like Notice Period, Current CTC and Expected CTC at
Machine Learning Engineer
Posted today
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Job Description
Responsive is looking for an ML Engineer with a strong background in Python, NLP, structured and unstructured data, and basic understanding of ML and DL algorithms/frameworks. The ideal candidate will have a Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics. The ML Engineer should be familiar with Linux and Git and have strong problem-solving and analytical skills. Additionally, the candidate should have a good understanding of mathematics.
Essential Responsibilities
- To develop and implement ML models and algorithms that improve the company's products and services.
- To Work with large datasets to analyze, model, and interpret data.
- To create and optimize NLP models to extract meaningful insights from unstructured text data.
- To collaborate with cross-functional teams to identify and solve complex business problems.
- To continuously monitor and improve the performance of ML models.
- To develop and maintain ML codebase, including version control using Git.
Education
Bachelor's degree in any quantitative discipline, such as Engineering, Computer Science, IT, or Statistics.
Experience
- 4-6 years of experience in Machine Learning
- Proficiency in Python is a must
Knowledge, Ability & Skills
- Comfortable with NLP techniques.
- Basic understanding of ML and DL algorithms/frameworks.
- Familiarity with Linux and Git.
- Good problem-solving and analytical skills.
- Good understanding of mathematics.
Machine Learning Engineer
Posted today
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Job Description
Job Description 1 – Machine Learning Engineer
Role: Machine Learning Engineer
Experience: 5+ years
Location: Pune, Bangalore, Hyderabad, Mohali, Chennai, Bhubneshwar
Role Summary
We are seeking a Machine Learning Engineer to design, develop, and deploy advanced AI/ML models that drive innovation and business value. The ideal candidate will have hands-on experience in building scalable ML pipelines, applying generative AI frameworks, and optimizing models for performance and efficiency.
Key Responsibilities
- Design, develop, and test AI/ML models adhering to architecture and coding standards.
- Perform data preprocessing, feature engineering, and model evaluation to ensure accuracy and reliability.
- Write technical specifications, documentation, and reusable code .
- Conduct code reviews and provide constructive feedback to peers.
- Collaborate with cross-functional teams to integrate ML models into production applications.
- Optimize models for performance, scalability, and low latency .
- Stay updated with the latest advancements in AI/ML, deep learning, and generative AI frameworks .
Required Skills
- Strong knowledge of Machine Learning algorithms and techniques.
- Proficiency in Python for ML/AI development.
- Experience with Generative AI frameworks (LLMs, Transformers, etc.) .
- Expertise in data analysis, feature engineering, and model evaluation techniques .
- Familiarity with code review practices and collaborative development tools .
- Knowledge of cloud platforms (AWS, Azure, or GCP) is a plus.
Job Description 2 – ML/Backend Engineer
Role: ML/Backend Engineer
Experience: 5+ years
Location: Pune, Bangalore, Hyderabad, Mohali, Chennai, Bhubneshwar
Role Summary
We are looking for an ML/Backend Engineer who can combine expertise in machine learning with backend system development. The role involves designing AI/ML models while ensuring seamless backend integration, API development, and efficient data handling for production-ready deployments.
Key Responsibilities
- Design, develop, and test AI/ML models and solutions aligned with system architecture.
- Implement backend logic, APIs, and data pipelines for smooth ML model deployment.
- Work on database design and management (SQL/NoSQL) to support large-scale ML applications.
- Conduct code reviews , ensuring performance and maintainability.
- Collaborate with other developers, data scientists, and product teams to integrate solutions.
- Ensure backend systems are scalable, secure, and cloud-ready .
- Stay up-to-date with emerging ML, backend, and cloud technologies .
Required Skills
- Proficiency in Python for both ML and backend development.
- Hands-on experience with Machine Learning algorithms and Generative AI frameworks .
- Strong knowledge of FastAPI (or similar Python frameworks) for API design.
- Expertise in database management (SQL/NoSQL) .
- Experience with cloud platforms (AWS, Azure, or GCP) for deployment.
- Strong understanding of data analysis, feature engineering, and model evaluation .