Top Machine Learning Engineer Jobs in Mumbai

Design and implement AI models, operationalize ML models, develop CI/CD pipelines for ML workflows, and provide technical guidance while ensuring data security compliance.

Senior technical leader defining evaluation-driven development, modeling strategy, MLOps and platform direction on AWS. Oversees multiple agile release cycles, ensures measurable business impact, mentors data scientists, sets governance for evaluation, synthetic data, validation, cost and compliance across the ML portfolio.

Create and review realistic, locale-specific robotics and natural sciences tasks in Marathi; apply scoring rubrics; review and score AI and human responses; produce gold-standard solutions and expert feedback.

As an AI Data Expert, you'll evaluate AI-generated outputs, review text, analyze multimedia, and provide structured feedback based on cultural standards.

Create, adapt, and score domain-specific robotics tasks and rubrics in Telugu to evaluate AI systems; review submissions for accuracy, regulatory alignment, and produce gold-standard solutions and expert feedback.

Create and review realistic, domain-specific robotics tasks in Hindi; apply scoring rubrics; evaluate AI and human responses for accuracy, regulatory alignment, and professional quality; and produce gold-standard solutions and expert feedback.

Create and review realistic, locale-specific robotics and natural sciences tasks in Tamil to evaluate AI systems; apply scoring rubrics, review and score submissions for accuracy and regulatory alignment, and produce gold-standard solutions and expert feedback.

The Senior Manager, Machine Learning leads the Conversation Memory team, focusing on developing foundational AI features, ensuring operational excellence, mentoring engineers, and managing project timelines for ML solutions.

Lead advanced statistical analyses and machine learning projects, partner with cross-functional teams to design data-driven solutions, manage large datasets with governance best practices, build predictive models to forecast trends, and communicate insights to stakeholders.

Design, build, and deploy generative AI solutions including RAG pipelines, agentic systems, and fine-tuned language models. Lead end-to-end AI projects from prototyping to cloud deployment, collaborate with cross-functional teams, and evaluate emerging AI technologies while ensuring scalable, production-grade engineering and ML ops practices.

Design and deliver ML solution architectures in healthcare. Lead model development, deployment and operationalization with cross-functional teams, communicate insights to clients, mentor senior staff, drive technical discussions, and identify sales opportunities.

Senior Databricks MLOps Engineer responsible for automating the end-to-end ML lifecycle: CI/CD, packaging, deployment, scheduling, monitoring, and reproducible experiments. Build frameworks and pipelines, integrate embedding/LLM components (RAG, vector DBs, LangChain), optimize ML workloads, and collaborate with data scientists and platform teams to productionize models for Claims Payment Integrity.

As a Junior-Midlevel Developer, you will develop, maintain, and enhance an AI-powered education platform, collaborating with teams to build software and optimize performance.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

The ROR Developer will focus on software engineering practices, design, data structures, algorithms, and deliver projects with responsibility, while keeping pace with industry trends.

The Data Scientist will leverage critical thinking and data analysis skills to develop Machine Learning models for detecting financial crime risks and synthesizing data requirements.

Lead the ML technical vision and roadmap, design and build agentic AI and NLP systems (LLMs, speech models), implement data pipelines, deploy models at scale, define feature roadmaps, collaborate cross-functionally, mentor engineers, and stay current on ML research.

Build and deploy ML models and systems powering autonomous AI agents for loan servicing and collections. Train and fine-tune LLMs, design evaluations and monitoring, tune prompts, integrate APIs, debug real-time issues, and own features from definition through production.

Lead the design, development, deployment, and optimization of AI-driven applications, especially RAG-based chatbots and generative AI solutions. Build scalable systems with Python and Java, deploy them on AWS and Azure, and apply machine learning, deep learning, NLP, vector databases, embeddings, and LLM integrations. Collaborate with cross-functional teams, manage technical deliverables, mentor engineers, ensure quality through testing and optimization, and adopt emerging AI technologies.

Lead ML architecture and solution design for NLP, computer vision, and generative AI projects. Define technical designs, review implementations, run POCs, guide developers, and ensure scalable, secure, and ethical deployments using cloud, MLOps, and model deployment pipelines.

Lead design and delivery of ML solutions across NLP, vision, and generative AI. Convert business needs into architecture and designs, guide developers, run POCs, ensure scalability, security, MLOps, and responsible AI best practices, and build/deploy AI agents and LLM-based systems.

Design and deploy AI/ML solutions on Snowflake, build ML pipelines and POCs using SQL/Python/APIs, advise customers and systems integrators, enable teams via best practices, collaborate with Product/Engineering, and travel to customer sites (~25%).

Lead the product strategy and execution for an AI-first Email Marketing platform. Own Email Builder UX, AI-native content generation, Sequence AI, delivery/automation, experimentation, reporting, consent management, and cross-functional alignment to drive adoption, engagement, and revenue.

Own end-to-end enterprise sales across Southeast Asia: prospecting, partner-led growth, channel management, demos, negotiation, forecasting, and closing. Build territory and partner plans, hit revenue quotas, represent CloudSEK to CISOs, collaborate with engineering, marketing and customer success, and manage onboarding and contract negotiations.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.