Top AI & Machine Learning Jobs in Mumbai, MH

Build, operate, and improve end-to-end Agentic AI/ML pipelines and a map compilation platform for HD maps. Implement scalable CI/CD/CT for ML, design fault-tolerant orchestration, deploy containerized models in cloud-native environments, monitor model performance and data drift, manage model lifecycle/versioning, drive IaC and cloud reliability, and collaborate on architecture and incident resolution.

Design, build, and operate end-to-end MLOps infrastructure and pipelines for training, evaluation, deployment, monitoring, and retraining. Own model-serving for batch and real-time workloads, implement CI/CD, containerized orchestration, model/data versioning, observability, and drift detection. Optimize GPU/compute utilization, enable reproducible research-to-production workflows, and evaluate emerging MLOps tools while partnering with researchers and platform teams.

Design, build, and productionize machine learning and generative AI solutions. Develop scalable data pipelines, deploy and monitor models, optimize performance, and collaborate with Product, Data Operations, and Engineering to translate business problems into reliable AI-powered applications.

Design, develop, and deploy ML models (classification, forecasting, NLP, LLMs); build scalable data pipelines; integrate AI into production; collaborate with Data Ops, Product, and Engineering; improve model performance and scalability; and implement model monitoring, governance, and lifecycle management.

Lead design and deployment of machine learning and analytics solutions for global-scale map-making. Build and test predictive and statistical models, drive process automation on Big Data infrastructure, mentor data science teams, and collaborate with researchers, developers, architects, and stakeholders to deliver scalable map-related ML systems.

Lead development and deployment of scalable machine learning and analytics solutions for global map-making. Design process automation, build predictive and statistical models, lead modeling teams, collaborate with researchers, developers, architects, and customers, and work with big-data pipelines and point-cloud/computer-vision methods.

Lead design and deliver efficient perception models for road scenes, optimize models for edge devices (Jetson, Snapdragon, ARM), improve real-time inference via quantization/pruning/distillation, convert/deploy with TensorRT/ONNX, build scalable training/evaluation with PyTorch or TensorFlow, and collaborate with embedded and software teams to produce production-ready edge AI systems.