Top Machine Learning Jobs in India

Lead design, implementation, testing, deployment and maintenance of high-quality distributed systems for TMS/WMS. Own technical direction and roadmap, hire and mentor engineers, deliver features in an Agile/DevOps environment, and apply ML and geolocation integrations to improve service performance, reliability, cost, and security.

Investigate, develop, implement and deploy applied machine learning and statistical models to solve client problems. Translate complex analyses into actionable insights, manage stakeholders, communicate results, and connect work to customer experience to deliver measurable impact.

Design and deploy production-ready AI and machine learning applications using Microsoft Azure Machine Learning and cloud or on-premises pipelines. Integrate generative AI, deep learning, neural networks, chatbots, and image processing. Lead solution development, monitor model performance, optimize AI pipelines, coordinate stakeholders, make technical decisions, and mentor team members.

Develop production-ready AI applications and systems using cloud AI services, generative AI models, and large language models. Responsibilities include designing scalable AI solutions, applying deep learning, NLP, chatbots, neural networks, and image processing, collaborating across teams, making technical decisions, mentoring junior engineers, and improving workflows. The role requires subject matter expertise in LLMs and experience deploying AI solutions on cloud platforms.

Design and deploy production-ready AI applications using generative AI, cloud services, and on-premises infrastructure. Build scalable AI pipelines and solutions involving deep learning, neural networks, chatbots, conversational AI, and image processing. Lead technical decisions, coordinate cross-functional teams, mentor junior engineers, and serve as a subject matter expert while aligning AI implementations with business objectives.

Develop AI-driven applications and production-ready systems using large language models, generative AI, cloud AI services, and deployment pipelines. Responsibilities include designing and implementing AI solutions, integrating them into existing workflows, and applying deep learning, neural networks, chatbots, natural language processing, and image processing. The role requires independent execution, subject matter expertise, team participation, and cross-functional collaboration.

Develop AI and machine learning applications using cloud AI services and production-ready pipelines. Apply generative AI and large language models, with potential work in deep learning, neural networks, chatbots, and image processing. Design APIs, preprocess data, evaluate emerging AI technologies, collaborate across teams, make technical decisions, and mentor team members. The role requires expertise in LLMs, deep learning frameworks, cloud AI platforms, and production implementation.

Develop and deploy production-ready AI and machine learning applications using Generative AI models, cloud AI services, and cloud or on-premises pipelines. Work with deep learning, neural networks, chatbots, and image processing. Collaborate across teams, make technical decisions, mentor junior engineers, manage team performance, and evaluate new technologies to improve system efficiency and functionality.

Design and develop production-ready AI and machine learning applications using cloud or on-premises pipelines. Integrate generative AI, deep learning, neural networks, chatbots, and image-processing solutions. Manage model lifecycle activities including training, validation, deployment, monitoring, and optimization. Collaborate with stakeholders, contribute technical solutions, document processes, and mentor junior team members while independently serving as a subject matter expert.

Perform remote, part-time data tasks to improve AI content in Marathi, including data collection, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

Lead quality control for annotated construction data (CAD/BIM/MEP). Review and validate annotator outputs, perform AutoCAD annotation, collaborate with CV/ML engineers to improve model-data alignment, manage and mentor annotators, and drive process/tooling improvements with engineering leads.

Develop, implement, and deploy scalable machine learning models for healthcare solutions. Collaborate cross-functionally to integrate models, analyze data to improve performance, ensure data quality, and stay current with ML advancements to support patient care and operational efficiency.

Develops and deploys production-ready AI applications using generative AI, cloud or on-premises pipelines, deep learning, neural networks, chatbots, and image processing. Responsibilities include designing technical solutions, optimizing AI models, collaborating with teams, documenting implementations, contributing to problem solving, and mentoring junior team members. Requires independent execution, subject-matter expertise, at least three years of generative AI experience, and 15 years of full-time education.

Design, build, and maintain production-ready AI/ML applications and pipelines (cloud or on‑prem). Integrate generative AI and deep learning solutions, deploy and monitor models, optimize system performance, and mentor junior team members while collaborating with stakeholders.

Design and implement production-ready AI/ML pipelines using Dataiku DSS and cloud AI services. Integrate generative AI and deep learning solutions, lead and manage teams, ensure scalable, high-quality deployments, collaborate across teams, and drive technical decisions and knowledge sharing.

Designs, builds, and deploys production-ready AI/ML systems using cloud or on-prem pipelines. Integrates generative AI and deep learning models, leads teams, coordinates stakeholders, and ensures scalability, robustness, and operational performance of ML solutions.

Develop and deploy production-ready AI/ML applications using cloud AI services and SageMaker. Integrate generative AI models and work on deep learning, chatbots, and image processing. Lead and mentor team members, make technical decisions, and collaborate across teams to deliver robust AI solutions.

Design and build production-ready AI/ML applications and pipelines, integrate generative AI and advanced models, lead and mentor teams, collaborate with stakeholders, and optimize data workflows for scalable deployments on cloud or on-prem environments.

Develop production-ready AI applications using cloud AI services and generative AI models. Apply deep learning and neural networks (TensorFlow/PyTorch), perform data preprocessing and feature engineering, and lead teams to deliver scalable chatbot and image-processing solutions.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Design, build, and maintain scalable, monitored ML/data pipelines and platforms; integrate ML models into production; collaborate with data scientists and stakeholders; automate orchestration, monitoring, and CI/CD; ensure data quality and documentation in a hybrid matrix environment.

Lead development and delivery of generative AI products across the firm: define roadmaps, translate user needs into features, collaborate with engineering and research, manage stakeholders, use feedback and market insights to prioritize and iterate, and help shape overall AI strategy to deliver measurable business value.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Develop and apply NLP and text-mining solutions using Java stack; perform entity and text extraction, web crawling, and ML model work. Use NLP tools (GATE, OpenNLP, Lucene), work on Unix/Linux, and collaborate with a team. Big-data/Hadoop experience preferred.

Lead AI R&D: design, develop, deploy scalable AI/ML and deep learning solutions for structured and unstructured data in BFSI product areas. Manage technical teams, mentor staff, integrate AI into products, ensure model scalability and production-readiness, and monitor AI trends and methodologies.