Top Artificial Intelligence Jobs in Delhi

The role involves collaborating with Data Science teams to implement and manage ML models, designing GenAI solutions, and automating ML operations, while establishing best practices in ML lifecycle management.

The Technical AI Product Manager at CoinMarketCap will prototype AI solutions, identify user pain points, and collaborate with Engineering to validate and scale AI products in the crypto space.

The AI/ML Engineer II is responsible for designing, developing, and deploying AI/ML solutions. They work closely with product management and engineering teams to translate business problems into scalable AI systems, focusing on model optimization, cloud deployment, and cross-functional collaboration.

The AI Architect will lead technical execution of AI strategies, design autonomous agent systems, and guide clients in deploying Generative AI solutions.

The Product Analyst will identify growth opportunities, evaluate product changes through A/B testing, build dashboards, and communicate insights for data-driven decisions.

The role involves creating original math problems, auditing existing content for accuracy, operating AI tools for content generation, and collaborating with the academic team to deliver pedagogically sound math resources.

The Head of Product will lead the AIVM platform development, managing product strategy, execution, and cross-functional collaboration while focusing on AI and blockchain technologies.

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

The AI Engineer will develop, deploy, and optimize AI solutions using Google's Gemini, working with machine learning models and data pipelines in a client-focused environment.

The AI Engineer will design and automate business processes using n8n, manage workflows, and collaborate with teams on technical requirements and solutions.

Lead Aftershoot's AI/ML function: define roadmap, drive end-to-end computer vision model development, optimize models for edge/mobile, build and mentor an ML research and engineering team, and translate AI advancements into product features.

Build and deploy autonomous AI agents and internal copilots that research, enrich, reason, and execute GTM workflows. Implement RAG with embeddings and vector DBs, integrate agents with HubSpot and internal systems, automate data pipelines and scraping, and own agent systems end-to-end from prototype to production.