Top Machine Learning Jobs in India

Lead architecture, development, and deployment of scalable ML and Generative AI solutions. Own end-to-end model lifecycle, MLOps pipelines, cloud-native deployments (AWS), vector DB ingestion, LLM/embedding selection, CI/CD, and mentor junior engineers while collaborating with cross-functional teams.

Design, prototype, and deploy AI/ML and computer-vision solutions for production factories. Perform feasibility studies, collaborate globally with research teams, support operational excellence, and integrate systems with existing hardware to improve production processes.

Design and develop machine learning infrastructure and models, support product teams, build scalable data services, and promote collaboration within a diverse engineering team.

Design, develop, and productionize machine learning models (classification, regression, clustering). Work with large datasets, SQL, and cloud platforms (Azure/GCP). Apply generative AI/LLMs, follow software engineering practices, and collaborate on Databricks/MLflow pipelines. Prefer FinTech/credit card experience.

As a Technical Program Manager, you will lead cross-functional initiatives to enhance Guidewire's Data & ML Platform, focusing on AI, cloud, and data services while ensuring project delivery and operational excellence.

This role involves developing scalable AI/ML models, working with cross-functional teams, following agile processes, and maintaining deployed solutions.

Lead a team of AI QA Engineers, driving QA strategy for ML models, develop automated test frameworks, validate APIs, and ensure high quality in AI solutions.

The role involves developing scalable AI/ML models, collaborating with cross-functional teams, maintaining production solutions, and driving experimentation in AI/ML techniques.

The AI ML Engineering Manager at TaskUs will design machine learning models, mentor a team, and leverage AI technologies while ensuring product quality and timeliness.

As a Sr. ML Engineer, you'll design, build, and deploy ML solutions for various industries, leading the full ML lifecycle and collaborating with clients.

Lead initiatives to enhance the ML platform, mentor junior engineers, build scalable ML models, and ensure code quality while driving innovation in a startup environment.

The Machine Learning Engineer will develop and innovate ML models and their infrastructure, collaborate, mentor, and take ownership of impactful projects.

Lead and grow Gracenote's AI/ML and Data Science teams, establish technical rigor and operating cadence, manage cross-functional stakeholder delivery, oversee ML/GenAI/NLP/computer vision research and production deployments, drive MLOps and QA, automate recurring analyses, and evolve predictive analytics and market-research methodologies for media measurement.

Lead AI-driven automation projects, mentor team members, evaluate technology solutions, and ensure successful deployment of AI models to enhance business operations.

The Associate Systems Developer will support application development and maintenance activities, requiring programming in C#, and working with .NET technologies and Azure DevOps.

The Senior Machine Learning Engineer will lead the architecture and implementation of a generative AI-powered video creative platform, focusing on optimizing video ad creation while collaborating with multiple teams.

As a Senior Machine Learning Ops Engineer, you will design and maintain scalable ML platforms, run A/B tests, and mentor team members.

Responsible for building and optimizing ML microservices, writing production code in Python, maintaining APIs, and collaborating with teams to deploy ML features.

The Product Manager will define and drive AI-powered statistics for life sciences, collaborate across teams, engage with customers, and support market differentiation strategies.

Design, build, deploy, and monitor LLM-based GenAI applications and agentic systems. Implement RAG pipelines, vector DB integrations, AI backends (FastAPI/Flask), chat UIs, and cloud MLOps ensuring performance, scalability, security, and Responsible AI compliance.

Design and develop end-to-end AI capabilities in NLP, optimize ML models and systems, and collaborate with cross-functional teams.

As an AI/ML Engineer, you will develop machine learning models, collaborate with teams, preprocess data, and optimize ML pipelines. Additionally, you will mentor junior members and contribute to AI/ML strategies.

The Associate Engineer will design and develop AI workflows and LLM-powered applications, integrating various technologies and collaborating in an agile team environment.

Maintain and optimize production algorithms and services: profile and tune CPU/memory/I/O, add parallelism, triage/fix bugs, build and maintain REST APIs (Django/DRF or FastAPI), implement tests and CI/CD, benchmark scalability and cost, and collaborate with product/data/QA to meet SLAs.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.