3,057 AI Driven Robotics jobs in India
Machine Learning
Posted today
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• Background in natural language processing and/or machine learning -
• Strong Computer Science fundamentals (algorithms, data structures) -
• Industry experience developing multi-threaded applications -
• Mathematical background (probability & statistics) a strong plus
• Knowledge of SQL, PL/SQL and standard RDBMSs a plus
Machine Learning
Posted today
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Job Description
What You will Do
Implement models and algorithms on Databricks and H2O
Write in Python or other languages to deliver a wide variety of Machine Learning & Data Science solutions
Building tools to accelerate feature experimentation and exploration with lineage, data privacy protection and easier model performance debugging.
Stay abreast of new tools, packages, and Machine Learning techniques while consistently pushing the limit of what is possible to deliver the best solutions for clients
Manage AWS assets including compute, storage, ID management.
Building ML-as-a-service, with the purpose of taking experiments to production quickly.
Share learnings and project findings with the wider Workday Machine Learning Community
Willing to work across multiple time zones.
What You will Bring
5+ years of technology industry experience
3 - 4+ years of experience implementing models or machine learning algorithms in production
Proficient experience writing SQL, Spark
Experience on any of these cloud platforms (AWS, Azure, GCP)
Experience developing models and other data science work with Python (preferred) or R
(preferred) Familiarity with ML Ops pipelines or CI/CD implementations
(Optional) Quantitative graduate degree
(Optional) One or more of the following other languages: Python, R, JavaScript, Go, Scala
(Optional) Experience acting as a project manager
**About Virtusa**
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 30,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.
Machine Learning Engineer
Posted 2 days ago
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Job Description
Work Area: Software-Design and Development
Expected Travel: 0 - 10%
Career Status: Professional
Employment Type: Regular Full Time
Career Level: T2
Hiring Manager: Ismail Basha
Recruiter Name: Rajasree Saha
Additional Locations:
As market leader in enterprise application software, SAP helps companies of all sizes and industries innovate through simplification. From the back office to the boardroom, warehouse to storefront, on premise to cloud, desktop to mobile device - SAP empowers people and organizations to work together more efficiently and use business insight more effectively to stay ahead of the competition. SAP applications and services enable customers to operate profitably, adapt continuously, and grow sustainably.
**Senior Machine Learning Engineer**
**POSITION OVERVIEW**
We are looking for an experienced cloud developer to support us in the development of digital assistants and agentic flows in the context of Public Cloud. If you want to become part of our motivated team and develop an intelligent application based on cutting-edge technology in a cloud-native architecture, you will find an exciting opportunity to take end-to-end ownership of features from design and development through to quality assurance, deployment, and support:
**Product Technology Stack**
+ Strong proficiency in VSCode, Python , Java/SpringBoot , Joule, Agents, LLMs, Jupyter notebooks, BTP and ABAP and extensive experience in software engineering.
+ Knowledge is any functional domain especially Finance will be an advantage
+ Expertise with CI/CD tools.
+ Experience in cloud development, with a preference for SAP Business Technology Platform (BTP).
+ Experience in prompt engineering with large language models (LLMs).
+ Strong understanding of AI and machine learning concepts, with proficiency in YAML for configuration management
**What you'll do**
+ Work with data scientists, software architects, and engineers to design and implement digital assistant functionalities on Joule
+ Work with data scientists, software architects, and engineers to design and implement e2e agentic flows and collaborate also with domain experts from PM and LoBs.
+ Focus on scalability, reliability, and performance of applications using LLM and allied technology and framework.
+ Implement automated deployment and monitoring processes using CI/CD tools, preferably Jenkins.
+ Enhance workflows to improve efficiency and user experience.
+ Keep abreast of the latest developments in AI, LLMs, and software development.
+ Integrate digital assistants and agentic flows with cloud platforms.
+ Use YAML, for effective configuration management of digital assistant applications
**What you bring**
+ Create and sustain GenAI digital assistants using LLMs and RAG
+ Master's/bachelor's degree in computer science, data science, engineering, or a related field.
+ Total work experience 4-8 years
+ Strong analytical and problem-solving skills
**Meet the Team**
**ABOUT SAP S/4HANA Finance Product & Engineering**
Within the SAP S/4HANA Finance Product & Engineering team, we are a team of passionate AI mavericks who are on the path of setting SAP ecosystem as a frontrunner in the AI/ML arena. We work on multiple projects across the S/4HANA finance area like Joule, Agents, ISLM ,classic AI/ML projects and Customer Agents.
**SAP'S DIVERSITY COMMITMENT**
To harness the power of innovation, SAP invests in the development of its diverse employees. We aspire to leverage the qualities and appreciate the unique competencies that each person brings to the company.
SAP is committed to the principles of Equal Employment Opportunity and to providing reasonable accommodations to applicants with physical and/or mental disabilities. If you are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team:
Successful candidates might be required to undergo a background verification with an external vendor.
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy ( .
Machine Learning Engineer
Posted 5 days ago
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Job Description
**Location:** Hybrid
**Job Type:** Full-time
**About Us:**
Ralliant is at the forefront of leveraging data and AI technologies to drive innovation across Precision Tech Industries. We aim to solve real-world challenges by combining advanced machine learning, cloud computing, and generative AI to deliver cutting-edge solutions. We're looking for a talented and passionate **MLE** to join our dynamic team and help us continue to push the boundaries of AI.
· **Model Deployment & MLOps:**
+ Design, build, and maintain machine learning pipelines, ensuring continuous integration and deployment (CI/CD) of models in production environments.
+ Deploy machine learning models as APIs, microservices, or serverless functions for real-time inference.
+ Manage and scale machine learning workloads using Kubernetes, Docker, and cloud-based infrastructure (AWS, Azure, GCP).
· **Automation & Scripting:**
+ Automate routine tasks across the ML lifecycle (data preprocessing, model training, evaluation, deployment) using Python, Bash, and other scripting tools.
+ Implement automation for end-to-end model management and monitor pipelines for health, performance, and anomalies.
· **Cloud Platforms & Infrastructure:**
+ Utilize cloud platforms (AWS, Azure, GCP) to optimize the scalability, performance, and cost-effectiveness of ML systems.
+ Leverage Infrastructure as Code (IaC) tools like Terraform or CloudFormation to provision and manage cloud resources effectively.
· **Data Pipelines & Integration:**
+ Build and maintain robust data pipelines to streamline data ingestion, preprocessing, and feature engineering.
+ Work with both structured and unstructured data sources and databases (SQL, NoSQL) to feed data into ML models.
· **Monitoring, Logging & Troubleshooting:**
+ Set up monitoring and logging systems to track model performance, detect anomalies, and maintain system health.
+ Diagnose and resolve issues across the machine learning pipeline and deployed models.
· **Collaboration & Communication:**
+ Collaborate closely with data scientists, software engineers, and business stakeholders to ensure machine learning models meet the required business objectives and performance standards.
+ Effectively communicate complex ML concepts and technical details to non-technical stakeholders.
· **GenAI & AI Agents Expertise:**
+ Stay up to date with the latest trends in Generative AI (e.g., GPT models, Diffusion models) and AI agents, and bring this expertise into production environments.
+ Design and deploy advanced GenAI solutions, ensuring they are aligned with business needs and ethical AI principles.
· **Security & Compliance:**
+ Implement robust security measures for machine learning models and ensure compliance with relevant data protection and privacy regulations.
+ Address vulnerabilities, ensuring safe and secure deployment of models in production environments.
· **Optimization & Cost Management:**
+ Optimize machine learning resources (compute, memory, storage) to achieve high performance while minimizing operational costs.
+ Regularly review and improve the efficiency of machine learning workflows.
· **Testing & Validation:**
+ Develop and execute rigorous testing and validation strategies to ensure the reliability, accuracy, and fairness of deployed models.
+ Use automated testing frameworks to continuously validate model performance.
**Required Skills & Qualifications:**
+ **Education** : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
+ **Experience** :
+ Proven experience (3+ years) in machine learning engineering, MLOps, or related fields.
+ Experience with deploying and managing machine learning models in production using tools like Kubernetes, Docker, and CI/CD pipelines.
+ Hands-on experience with cloud platforms (AWS, Azure, GCP) and infrastructure automation tools (Terraform, CloudFormation).
+ Strong coding experience in Python, Bash, or other scripting languages.
+ Expertise in Generative AI models (e.g., GPT, GANs) and their deployment at scale.
+ Experience working with databases (SQL, NoSQL) and building data pipelines.
+ **DevOps & CI/CD** :
+ Knowledge of DevOps tools and practices, including version control (Git), automated testing, and continuous integration/deployment.
+ **AI Agents** : Familiarity with the latest AI agent frameworks and their deployment in real-world applications.
+ **Data Science Concepts** : Solid understanding of GenAI,NLP, Computer Vision, machine learning algorithms, data structures, and model evaluation techniques.
+ **Problem-Solving** : Strong troubleshooting and debugging skills to quickly identify and fix issues within ML pipelines and deployments.
+ **Collaboration & Communication** : Excellent communication skills with the ability to work in a cross-functional team and explain technical concepts to non-technical stakeholders.
**Preferred Qualifications:**
+ Certification in Cloud Technologies (AWS, Azure, GCP) and MLOps platforms.
+ Experience with large-scale ML systems and distributed computing.
+ Understanding of ethical AI practices and AI fairness.
+ Familiarity with cutting-edge AI technologies like reinforcement learning, AI agents, and deep learning.
**Technical Skills:**
+ Proficiency in Python, R, or other relevant programming languages.
+ Strong knowledge of machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
+ Experience with SQL and cloud-native data processing tools (e.g., AWS Redshift, Azure Synapse, Spark).
+ Familiarity with DevOps practices and CI/CD pipelines for ML model deployment.
**Soft Skills:**
+ Strong communication skills with the ability to translate complex technical concepts into business-friendly language.
+ Problem-solving mindset, with the ability to approach challenges creatively and collaborate with diverse teams.
+ Leadership potential or experience mentoring junior team members.
**Preferred Qualifications:**
+ Certification or training in AWS (e.g., AWS Certified Machine Learning), Azure, or other cloud services.
+ Experience working with containerization technologies like Docker and Kubernetes for model deployment.
+ Exposure to the latest trends in AI ethics, explainability, and fairness.
**Company Overview:**
Join a dynamic and innovative team at Ralliant, a leader in producing high-tech measurement instruments and essential sensors. Our brands, including Tektronix, Qualitrol, Sensing Technologies and Pacific Scientific, are at the forefront of technological advancements, providing critical products that drive innovation across various industries. At Ralliant, we are committed to excellence and continuous improvement, delivering top-tier solutions that meet the evolving needs of our Operating Companies
**These are the traits we value:**
+ You are collaborative, proactive, adaptable, and gritty. You excel at facilitating and reconciling inputs across separated geo-located teams. You balance a passion for deep understanding of innovation with the ability to deliver extraordinary results.
+ Ability to Deliver Results: A track record for delivering results with concrete financial and operational objectives as well as the capacity to organize and direct a small team.
+ Entrepreneurial Attitude: A proactive outlook that provides the chutzpah needed to overcome barriers, creatively problem solve, and test conventional thinking.
+ Comfort with Ambiguity: A willingness and aptitude for spending time in and thriving with deep uncertainty and environments where there is no clear "right answer".
+ Passion for Innovation: A demonstrated interest and desire to participate in innovation through personal study, on-the-job initiative, or other endeavors.
+ Positive Outlook: A desire to look past the objections in search of the opportunity.
+ Strong Communication Skills: An ability to explain new concepts clearly and succinctly, able to negotiate and persuade others to your point of view.
+ A need for speed; demonstrated ability to make decisions quickly and to act upon them.
+ Alongside a team of entrepreneurial, high-performing, curious people, you'll deliver breakthrough solutions to drive sustainable growth for Ralliant
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
**Ralliant Corporation Overview**
Ralliant, originally part of Fortive, now stands as a bold, independent public company driving innovation at the forefront of precision technology. With a global footprint and a legacy of excellence, we empower engineers to bring next-generation breakthroughs to life - faster, smarter, and more reliably. Our high-performance instruments, sensors, and subsystems fuel mission-critical advancements across industries, enabling real-world impact where it matters most. At Ralliant we're building the future, together with those driven to push boundaries, solve complex problems, and leave a lasting mark on the world.
We Are an Equal Opportunity Employer
Ralliant Corporation and all Ralliant Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Ralliant and all Ralliant Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at
**About NewCo**
**Bonus or Equity**
This position is also eligible for bonus as part of the total compensation package.
Machine Learning Engineer
Posted 1 day ago
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Job Description
Job Summary:
We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI.
You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product.
Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad
Experience: 1–3 Years
Education: BE / B.Tech / M.Tech / MCA / M.Com
Key Responsibilities:
Model Development & Experimentation
- Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques.
- Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection.
- Apply statistical analysis to validate and interpret model results.
- Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC).
Data Handling & Feature Engineering
- Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs.
- Perform feature extraction, transformation, and selection tailored to specific ML problems.
- Implement data augmentation and enrichment techniques to enhance training quality.
Model Deployment & Productionization
- Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker).
- Containerize models using Docker and orchestrate deployments with Kubernetes.
- Implement monitoring, logging, and automated retraining pipelines for model health tracking.
Collaboration & Innovation
- Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment.
- Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3).
- Contribute to documentation, versioning, and knowledge-sharing across teams.
- Drive innovation and continuous improvement in AI/ML delivery and engineering practices.
Mandatory Technical Skills:
- Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
- Model Development: Deep Learning, NLP, Time Series, Computer Vision
- Cloud Platforms: AWS (especially SageMaker)
- Model Deployment: Docker, Kubernetes, REST APIs
- ML Ops: Model monitoring, performance logging, CI/CD
- Frameworks: LangChain (for GenAI), Transformers, Hugging Face
Preferred / Good to Have:
- Experience with Foundation Model tuning and prompt engineering
- Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations)
- Certifications: AWS Certified Machine Learning – Specialty
- Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases)
Soft Skills:
- Excellent communication and presentation abilities
- Strong analytical and problem-solving mindset
- Ability to work in collaborative, fast-paced environments
- Curiosity to learn emerging technologies and apply them to real-world problems
Machine Learning Engineer
Posted 1 day ago
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Job Description
Machine Learning Engineer
Posted 2 days ago
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Job Description
Designation: - ML / MLOPs Engineer
Location: - Noida (Sector- 132)
Key Responsibilities:
• Model Development & Algorithm Optimization : Design, implement, and optimize ML
models and algorithms using libraries and frameworks such as TensorFlow , PyTorch , and
scikit-learn to solve complex business problems.
• Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy,
scalability, and efficiency while fine-tuning hyperparameters.
• Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitable
format for model training and evaluation, applying industry best practices to ensure data
quality.
• Feature Engineering : Conduct feature engineering to extract meaningful features from data
that enhance model performance and improve predictive capabilities.
• Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deploying
machine learning models into production environments, leveraging Azure Machine
Learning and containerization technologies like Docker and Kubernetes .
• Production Deployment : Develop and deploy machine learning models to production
environments, ensuring scalability and reliability using tools such as Azure Kubernetes
Service (AKS) .
• End-to-End ML Lifecycle Automation : Automate the end-to-end machine learning
lifecycle, including data ingestion, model training, deployment, and monitoring, ensuring
seamless operations and faster model iteration.
• Performance Optimization : Monitor and improve inference speed and latency to meet real-
time processing requirements, ensuring efficient and scalable solutions.
• NLP, CV, GenAI Programming : Work on machine learning projects involving Natural
Language Processing (NLP) , Computer Vision (CV) , and Generative AI (GenAI) ,
applying state-of-the-art techniques and frameworks to improve model performance.
• Collaboration & CI/CD Integration : Collaborate with data scientists and engineers to
integrate ML models into production workflows, building and maintaining continuous
integration/continuous deployment (CI/CD) pipelines using tools like Azure DevOps , Git ,
and Jenkins .
• Monitoring & Optimization : Continuously monitor the performance of deployed models,
adjusting parameters and optimizing algorithms to improve accuracy and efficiency.
• Security & Compliance : Ensure all machine learning models and processes adhere to
industry security standards and compliance protocols , such as GDPR and HIPAA .
• Documentation & Reporting : Document machine learning processes, models, and results to
ensure reproducibility and effective communication with stakeholders.Required Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related
field.
• 3+ years of experience in machine learning operations (MLOps), cloud engineering, or
similar roles.
• Proficiency in Python , with hands-on experience using libraries such as TensorFlow ,
PyTorch , scikit-learn , Pandas , and NumPy .
• Strong experience with Azure Machine Learning services, including Azure ML Studio ,
Azure Databricks , and Azure Kubernetes Service (AKS) .
• Knowledge and experience in building end-to-end ML pipelines, deploying models, and
automating the machine learning lifecycle.
• Expertise in Docker , Kubernetes , and container orchestration for deploying machine
learning models at scale.
• Experience in data engineering practices and familiarity with cloud storage solutions like
Azure Blob Storage and Azure Data Lake .
• Strong understanding of NLP , CV , or GenAI programming, along with the ability to apply
these techniques to real-world business problems.
• Experience with Git , Azure DevOps , or similar tools to manage version control and CI/CD
pipelines.
• Solid experience in machine learning algorithms , model training , evaluation , and
hyperparameter tuning
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Machine Learning Engineer
Posted 2 days ago
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Job Description
We are looking for talented Python Developers with 3 to 6 years hands-on experience in Natural Language Processing (NLP) and Generative AI Models to join our growing team working on innovative projects in enterprise scale AI applications and solutions.
Responsibilities:
- Design, evaluation, and best fit analysis of NLP / ML Models
- Design, fine-tuning, and deployment of open-source and API-based LLMs to solve real-world use cases
- Engage with clients for data preparation process, the subtleties of the fine-tuning procedure, and the challenges it presents.
- Lead efforts to address challenging data science and machine learning problems, spanning predictive modeling to natural language processing, with a significant impact on organizational success.
- Building data ingestion pipelines, handling various data formats such as JSON and YAML.
- Technical Qualifications:
- Strong in data collection, curation, and dataset preparation for ML Models (Classifiers / Categorization).
- Demonstrable expertise in area of data science or analytics (e.g., machine learning, deep learning, NLP, predictive modeling and forecasting, statistics).
- Strong experience in machine learning (unsupervised and supervised techniques) and experience in machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, Attention, Generative Models etc would be a plus.
- SQL expertise for data extraction, transformation, and analysis.
- Experience in building and maintaining scalable APIs using FastAPI / Flask frameworks.
- Proficiency in Python, with experience in libraries such as PyTorch or TensorFlow.
- Solid understanding of data structures, embedding techniques, and vector search systems.
- Experience in SQL / NoSQL databases including PostgreSQL, MySQL and MongoDB.
- Proficiency in Graph Databases Neo4j.
Generic Qualifications:
- Comfortable working with cross-functional teams product managers, data scientists, and other developers to deliver quality software solutions.
- Ensure software quality through code reviews, unit testing, and best practices for DevOps and CI/CD pipelines.
- Ability to manage time wisely across projects and competing priorities, meet agreed upon deadlines, and be accountable for work.
- Able to write maintainable and functionally tested modules.
- You should not hesitate in learning and building innovative solutions in newer technology stacks.
Qualifications:
B.Tech/B.E. in Computers, MCA, M.Sc Computer Science
Others:
- Candidate should be willing to relocate or commute to North Bangalore (Yelahanka) for work.
- Candidates who have 3 to 6 years of relevant experience can only apply.
Machine Learning Engineer
Posted 2 days ago
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Job Description
About KeyValue
KeyValue is a product development start-up, building highly scalable web and enterprise class software with a team of engineers specialized in Core Product Development.
We have the single-most vision of being the best product development start-up from India and to reach it, we have a single strategy: That of creating the Best of all Talent Pools and the Best of all Work Environments ever possible!
In our belief, every man is truly the owner of his/her work, his craft and can do the best when each sailor sailing on our ship can see the horizon that we all are sailing towards. For us, the best talents are the open-minded, ever-learning and all-embracing ones. We create, live and code on the cloud.
We are looking for a talented and motivated Machine Learning Engineer to join our growing team. In this role, you will play a key part in designing, developing, and deploying machine learning models to solve complex business problems. You will work closely with data scientists, software engineers, and product managers to bring innovative solutions to life.
What you will do:
- Design, develop, and deploy machine learning models for various applications (e.g., recommendation systems, fraud detection, natural language processing)
- Collaborate with data scientists to understand business requirements, translate them into technical specifications, and select appropriate algorithms
- Prepare and clean data for training and evaluation of machine learning models
- Train, test, and evaluate machine learning models to ensure accuracy, efficiency, and scalability
- Monitor and maintain deployed models in production, and identify opportunities for improvement
- Stay up-to-date on the latest advancements in machine learning research and best practices
- Communicate effectively with technical and non-technical audiences to explain complex concepts
What makes you a great fit ?
- 3-7 years of experience in machine learning engineering
- Proven experience in building and deploying machine learning models
- Strong understanding of machine learning algorithms and techniques (e.g., supervised learning, unsupervised learning, deep learning)
- Proficiency in Python
- Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Strong understanding of machine learning algorithms and techniques, as well as LLM architecture and functionalities.
- Excellent problem-solving and analytical skills
- Strong communication and collaboration skills
Bonus points:
- Experience with cloud platforms (e.g., AWS, GCP, Azure)
- Experience with MLOps tools and methodologies
- Open-source contributions
If you get to join us, what you get in the process would be invaluable opportunities to solve global problems with your talents and work with some of the most experienced software architects in the Indian IT industry and get mentored by them.
Machine Learning Engineer
Posted 2 days ago
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JD in AI/ML Developer
Job description
We are a leading technology firm with a subsidiary based in Pune, India, focusing on integrating cutting-edge artificial intelligence and machine learning technologies into customers applications. Our goal is to revolutionize how businesses operate by harnessing the power of AI to deliver innovative solutions. We are currently seeking a skilled AI/ML Developer to join our dynamic team and contribute to our mission of transforming the digital landscape.
Job Description
As an AI/ML Developer, you will be at the forefront of developing advanced applications integrating statistical models and AI-based models, including large language models like GPT, Llama and other proprietary and open-source/open-weight models as well as other types of ML models. You will work closely with our product and engineering teams to design, develop, and deploy AI-powered solutions that meet our clients' complex needs.
Key Responsibilities
Design and implement AI models using Python, focusing on leveraging various large language and statistical models using tools such as LangChain, ChatGPT, WatsonX etc.
Work with AI technologies to develop innovative solutions for real world problems.
Utilize tools like WatsonX, Watson Studio, Amazon sagemaker, Azure Machine Learning etc to enhance development workflows and model performance.
Collaborate with cross-functional teams to integrate AI/ML models into applications, ensuring they are scalable, efficient, and effective.
Stay abreast of the latest AI trends and technologies to ensure our solutions remain cutting-edge.
Mandatory Skills & Qualifications
Strong proficiency in Python and machine learning frameworks (Pytorch/Tensorflow).
Hands-on experience with LLMs (Large Language Models) and other neural networks.
Experience working with OpenAI GPT API or other open-source foundation models.
Familiarity with some of the following tools: WatsonX, langchain Watson Studio, Azure Machine Learning, AWS Sagemaker, Amazon Bedrock, Git, Docker
Proven track record of developing applications integrating both statistical and AI-based models.
We look forward to discovering how you can contribute to our team and mission!
Job Type: Full-time
Location Type:
- Hybrid
Schedule:
- Monday to Friday
Education:
- Bachelor's (Preferred)
Experience:
- Total work: 4 years (Preferred)
- Software development: 3 year (Preferred)
- Python: 3 year (Preferred)
- Machine Learning: 3 years (Preferred)
- Large Language Models: 2+ years (Preferred)
Ability to Commute:
- Pune, Maharashtra (Required)
Work Location: Hybrid