Top Artificial Intelligence Jobs in Mumbai

As a Senior/Staff AI Researcher, you'll lead research on Generative AI, implement algorithms, design models, and work with cross-functional teams to integrate findings into products.

The role involves reviewing and evaluating content based on guidelines, ensuring quality and consistency across annotations in a data annotation project for AI models.

Evaluate and annotate content according to guidelines, ensuring quality and consistency across tasks for an AI data project.

Review and assess content alignment with guidelines, ensuring quality and consistency in annotations across various types of content as part of a data annotation project.

Design, develop, and deploy machine learning models and AI solutions. Collaborate with teams for intelligent automation and conduct research on new AI technologies.

As an AI/ML Engineer, design, develop, and deploy machine learning models and AI solutions for fintech, ensuring integration with cloud platforms and robust data pipelines.

The Billing Associate will manage outbound insurance tasks, ensure AI performance, and support insurance setups while collaborating on product development.

The Solutions Engineer will develop AI agents, configure automations, lead technical onboarding for enterprise customers, and deliver BI reports to enhance customer success.

The AI Strategist will lead strategic enterprise accounts, shape AI strategies, engage with C-level executives, and collaborate cross-functionally to drive AI adoption.

The Ecosystem Growth Manager will drive growth by onboarding GPU providers, attracting AI developers, and establishing partnerships for AIVM's decentralized cloud infrastructure.

The role involves community building, brand development, strategic sourcing, and establishing relationships to attract talent in finance, healthcare, and law.

The role focuses on designing AI-driven workflows, developing user-friendly interfaces for complex backend logic, and enhancing UI/UX with real-time interactions and performance optimizations.

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

Build and scale Snowflake-native AI execution layers and orchestrated agent workflows. Implement RAG, embedding pipelines, vector retrieval, context-routing, monitoring, and integrations with enterprise data using SQL, Python, and DBT. Ensure scalable, observable, and governed AI systems across the organization.

The AI Engineer will develop, deploy, and optimize machine learning models for environmental and industrial applications, focusing on real-time object detection and classification.

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.

The Generative AI Engineer will develop AI agents utilizing LLMs, integrating them with tools, designing workflows, and enhancing AI systems for better reliability.