Top Artificial Intelligence Jobs in Mumbai

Lead the development and deployment of AI solutions in computer vision and NLP, mentor engineers, and drive MLOps practices.

Design and develop AI-based platforms for extracting and managing data from various sources, implementing data pipelines, and collaborating with stakeholders.

The Script Writer will create scripts and story outlines for various media, collaborate with creative teams, and utilize AI tools for story development.

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.

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.

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

Develop machine learning algorithms to analyze brain data, design experiments, build data visualization tools, and assist in AI model development for education.

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

The AI Manager will lead a global team in AI project delivery, manage AI roadmaps, oversee LLMOps pipelines, and engage with stakeholders while ensuring compliance and performance metrics are met.

The AI QA Specialist will design and execute test strategies for AI systems, validate model outputs, implement monitoring dashboards, and ensure compliance with safety standards.

Design and implement production-grade AI models and algorithms, lead AI initiatives across organizations, enhance Agentic AI capabilities, and collaborate with teams to develop high-impact AI features.

The MDM Specialist will design and implement master data management solutions, integrate AI workflows, and ensure data governance and quality across customer and vendor domains.

The MDM Specialist will architect and manage MDM platforms, ensuring data quality and governance while integrating AI workflows, optimizing for performance, and collaborating with business teams.

The AI Manager will lead global teams in AI delivery, ensuring strategic alignment with business goals, managing AI solutions, and upholding compliance standards.

As an AI QA Specialist, you will develop and execute test strategies for AI systems, validate outputs, monitor observability, and ensure compliance.

Lead AI initiatives and develop production-grade AI models using Agentic AI frameworks. Oversee Gemini Enterprise solutions, integrate secure systems, and enhance existing capabilities while collaborating across teams.

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

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

As a Lead Generation Specialist, you'll identify and qualify high-potential prospects in the Web3 and AI domains, employing outreach methods, CRM management, and market research to drive business development.

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

Design, build, and scale AI-powered automation workflows using n8n and similar tools. Integrate systems via APIs/webhooks, connect CRMs/marketing/databases/AI models, ensure scalability and reliability, debug and monitor automations, and document solutions while collaborating with business stakeholders.

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.

Design, build, and productionize internal AI-powered applications and workflows. Develop frontends, backend APIs, containerize and deploy via Snowflake SPCS, implement CI/CD, secure access, observability, and integrations with enterprise SaaS.

Lead design, development, and deployment of scalable ML solutions (recommendations, fraud detection, credit risk) on AWS. Build MLOps infrastructure, monitoring/alerting, support production models (on-call), mentor engineers, and collaborate with product teams to deliver and scale AI-driven features.

Design, build, and own AI-powered full-stack platforms and features from discovery through production. Embed AI into products and workflows, ensure reliability and security, support incidents, and mentor teammates.