Top Artificial Intelligence Jobs in Mumbai

Review and evaluate AI-generated outputs, provide annotations, and contribute cultural insights to improve AI training. Requires detail-oriented judgment and strong language skills.

The AI Engineer will develop and deploy advanced AI solutions focusing on generative capabilities, build context-aware AI agents, collaborate on data management, optimize AI model performance, and stay updated with AI advancements.

Design, train, optimize, and deploy production-ready computer vision models for image and video analytics. Prepare and manage datasets, integrate models into services, ensure performance and scalability, and collaborate with cross-functional teams while maintaining documentation and code quality.

Design, build, and operationalize AI-enabled data pipelines and production-grade AI applications using Python and Snowflake. Prepare and transform large datasets, develop features and embeddings, support deployment and monitoring of ML/LLM models, optimize Snowflake for AI workloads, and collaborate with data science and engineering teams to deliver scalable APIs and RAG-enabled data workflows.

Evaluate relevance of filters and options on desktop and mobile, ensuring they match customer queries and preferences. Follow guidelines, conduct online research, verify assessments for accuracy and consistency, and complete required training and qualification tests before starting. Work remotely on a flexible, part-time freelance schedule.

Review, evaluate, and annotate AI-generated text, image, audio, and video in Simplified Chinese. Perform quality checks, identify edge cases, participate in calibration, and provide feedback to improve annotation guidelines and datasets for generative AI models.

Review, evaluate, and annotate AI-generated text, image, audio, and video content for quality and guideline compliance. Perform quality checks, identify edge cases, participate in calibration activities, and provide feedback to improve datasets and annotation workflows for multilingual generative AI projects.

As an Applied Scientist, you'll develop advanced computer vision solutions using video data and Vision-Language Models, focusing on multimodal learning and real-world problem solving.

Lead enterprise AI strategy, design scalable AI solutions (LLMs, agentic AI, federated learning), evaluate emerging technologies, establish AI governance/Responsible AI, drive XAI adoption, collaborate with stakeholders, and implement advanced generative and orchestration solutions.

The Senior AI Engineer will lead the design and development of AI systems, mentor engineers, and drive innovation in AI technologies for gaming applications.

The AI Architect will design, implement, and oversee large-scale AI systems, ensuring they align with business goals and ethical standards. Responsibilities include architectural design, integration of AI models, and collaboration with data engineering. Requires over 10 years of experience in AI/ML implementations for large enterprises.

Lead a team for developing LLM and multimodal AI systems for healthcare. Ensure clinical safety, regulatory compliance, and effective deployment in telemedicine.

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 Strategic Projects Lead will oversee cross-functional projects, enhance product offerings, manage data operations, and collaborate closely with executive leadership to drive significant revenue growth in the Generative AI sector.

The Forward Deployed Senior Software Engineer will lead initiatives in building custom solutions and algorithms for healthcare data, collaborating with various teams to enhance customer experience and project delivery.

Design, scale, and maintain Salesforce Flow and orchestration workflows to automate seller, recruiter, and ops tasks. Implement Agentforce and AI-driven next-best-action processes, build repeatable automation frameworks across service lines, identify data quality gaps, create SLA triggers/escalations, run experiments, and maintain documentation and governance.

Develop AI solutions in Voice AI, Computer Vision, and Conversational AI. Architect and build AI systems for monitoring, analytics, and customer support across EV infrastructure.

Lead AI solutions development focusing on Voice AI, Computer Vision, and Conversational AI, enhancing customer support and monitoring platforms.

Develop, deploy, and scale AI/ML and generative AI solutions for a fintech platform. Design data models and pipelines, build agentic frameworks, integrate OCR and vector DBs, implement RAG, and champion MLOps and cloud deployment practices while mentoring teammates.

Build and operate backend services and infrastructure for LLM- and voice-driven healthcare applications. Implement APIs, productionize LLM workflows, deploy cloud containerized services, and monitor performance and reliability end-to-end.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Design, develop, and deploy advanced AI/ML models; manage large-scale data pipelines; build conversational and generative AI solutions; collaborate with stakeholders; monitor and optimize production models; document workflows and implement industry best practices.

Develop and execute organic marketing strategies to drive lead generation. Manage SEO, content-driven email campaigns, and webinars. Analyze campaign performance and optimize for improvements. Support revenue operations (RevOps) to align marketing with sales.

Design and lead enterprise-grade AI and Gen-AI integrations using the MCP (Model-Context-Prompt) framework. Architect LLM integrations, define prompt engineering and context strategies, evaluate models, design scalable secure solutions, oversee deployment/monitoring/optimization, mentor development teams, translate business needs into technical designs, and provide night-shift production support.

Gather and analyze stakeholder requirements and translate them into ServiceNow AI solutions (Virtual Agent, Predictive Intelligence, Now Assist). Collaborate with technical teams to implement AI-driven automation and agentic solutions, optimize workflows, monitor system performance, train users, and drive adoption while ensuring clear communication between business and technical stakeholders.