Top Artificial Intelligence Jobs in Delhi

The Senior AI Engineer II designs and develops scalable AI capabilities, optimizes ML models for business use cases, and leads data analytics talent within a collaborative environment.

The Senior Business Analyst will work closely with Project Managers and stakeholders to enhance project delivery, analyze business processes, and propose innovative solutions.

Perform data collection, evaluation, and annotation to improve AI-generated Kannada content. Tasks include pairwise comparisons, counting, object tagging and labeling across audio, video, images, and other data types.

Perform remote, part-time data tasks to improve AI content in Marathi, including data collection, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

Lead AI strategy and execution for content: research and prototype LLM and vision solutions, architect scalable AI pipelines to process millions of documents daily, manage production ML lifecycle (latency, prompt engineering, reliability), and mentor engineering teams to deliver mission-critical systems.

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.

As an AI Data Expert, you will evaluate AI-generated outputs, provide culturally relevant feedback, ensure content accuracy, and participate in quality assurance. This role requires strong analytical skills and attention to detail.

The AI Data Expert position involves evaluating AI outputs, generating content, and providing annotations to enhance AI training, all while considering cultural context. This role requires detail-oriented analysis, native language fluency, and strong English command.

The Project Manager will oversee multilingual data projects, manage resources, ensure quality, and coordinate with stakeholders to optimize AI model evaluations.

As an AI Data Expert, you'll evaluate AI-generated outputs, review text, analyze multimedia, and provide structured feedback based on cultural standards.

The role involves evaluating AI outputs, generating content, providing annotations, and ensuring quality through cultural and contextual awareness.

The role involves reviewing AI outputs, generating content, ensuring cultural accuracy, and providing structured feedback to improve AI models.

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

Lead the design and delivery of SAP Finance solutions, driving process excellence and innovation in a global organization, while mentoring junior team members.

Lead product development for an insurance-focused SaaS solution, collaborating across multiple teams and ensuring compliance and quality of deliverables.

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

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

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.

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.

As AI/Automation Ops Lead, ensure efficient operations of data pipelines, manage outages, oversee AI application performance, and mentor a team while maintaining 24/7 support.

Design and implement AI-enabled PLM architectures, lead integration with ERP and manufacturing systems, and ensure effective PLM processes and workflows.

Develop responsive front-end and robust back-end systems, collaborate on AI integrations, maintain databases, and implement DevOps practices. Emphasize on security and rapid prototyping in a dynamic, startup-like environment.

The AI Platform Engineer will design and optimize AI/ML infrastructure, automate pipelines, and manage Kubernetes for effective machine learning model deployment and collaboration.