Top Machine Learning Jobs in India

Lead the design and deployment of advanced machine learning models, mentor junior staff, and drive innovation in AI technology at Ema.

Lead end-to-end machine learning model development, including data sampling, training, deployment, and evaluation in an Agile environment. Utilize technologies such as Python and Azure to deliver large-scale machine learning solutions.

Develop ML solutions for decision-making using advanced modeling techniques. Collaborate with teams, design evaluations, and communicate results effectively. Strong coding skills and familiarity with ML tools required.

Lead the development and implementation of AI solutions, focusing on NLP and Generative AI, while mentoring a team of engineers and collaborating with cross-functional teams.

Design and implement scalable machine learning solutions, optimize ML workflows, deploy models using cloud services, and ensure CI/CD integration.

The Machine Learning Advisor will leverage AI and ML technologies to develop solutions for healthcare transformation, focusing on Generative AI and deep learning architectures.

You will design ML models to improve search and personalization, mentor junior engineers, and write maintainable code while collaborating with customers.

Lead development and deployment of ML-based search relevance models and pipelines. Improve query understanding, ranking, retrieval, and evaluation frameworks. Collaborate cross-functionally to productize search improvements and enable large-scale, robust search experiences.

The role involves designing and developing machine learning infrastructure for annotation, evaluation, and training models, focusing on scalable systems and efficient data workflows.

The role involves optimizing compiler performance, designing features for a high-performance architecture, and collaborating with hardware architects and model developers for effective ML inference.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

The AI/ML Tech Lead engages with clients to design and manage scalable AI/ML solutions, overseeing the complete delivery lifecycle and leading cross-functional teams.

Looking for an AI/ML Engineer to build and deploy forecasting models, develop ML models for optimization, and collaborate with business teams to translate problems into ML solutions.

The Machine Learning Engineer III will develop advanced machine learning and deep learning solutions for data extraction in ID verification. Responsibilities include designing algorithms, deploying models, and collaborating with teams to enhance security and user experience.

Design and deploy ML pipelines, develop CI/CD workflows, implement monitoring systems, collaborate with teams, and write scalable Python code for ML applications.

Design, build, and scale ML and generative AI solutions on the Elastic Stack: anomaly detection, data frame analytics, forecasting, vector/semantic/hybrid search, ELSER, and RAG. Integrate embeddings and LLMs, deploy transformer models via Eland, create inference ingest pipelines, design data models and ingestion flows, tune retrieval and relevance, and build Kibana dashboards and ML jobs for monitoring and alerting while partnering to operationalize features at scale.

The Senior Engineer will develop and deploy machine learning models and workflows, mentor junior engineers, and collaborate with cross-functional teams to improve patient care through innovative solutions.

Lead design and development of AI solutions to solve complex problems, build data pipelines, mentor teams, and incorporate AI research into products.

The role involves developing knowledge systems and AI pipelines, utilizing databases and machine learning models, and collaborating with data analysts.

As a Machine Learning Engineer, you will develop and maintain pipelines, deploy models as APIs, optimize ETL processes, and integrate ML with backend systems. Your focus will be on ensuring model reliability and data consistency in production environments.

Design and manage high-throughput ML systems for TravelAds, automate ML lifecycle processes, and lead cross-team ML initiatives with a focus on performance and reliability.

Design, build, and deploy production-grade ML systems (NLP and Generative AI), own MLOps and observability, solve complex unstructured data problems, mentor engineers, and collaborate cross-functionally to deliver scalable, reliable ML solutions.

Lead definition and execution of AI/ML initiatives across semiconductor design flows, deploying agentic AI for frontend and backend EDA tasks. Build scalable data and model pipelines, integrate AI into engineering toolchains, measure ROI via KPIs, and grow a high-performance team while aligning with enterprise AI governance.

Seeking a Machine Learning Engineer to work on workforce development and artificial product development, applying machine learning and deep learning concepts.

Design and implement agentic architectures for humanoid robots, collaborating with teams to enhance performance, safety, and reliability through advanced methodologies.