Top Artificial Intelligence Jobs in Pune

Lead technical development of AI solutions for finance automation, mentor teams, integrate AI with enterprise systems, and present to executives.

As a Senior Agentic AI Lead, you will manage the agentic AI domain, engage with customers, oversee the AI lifecycle, and ensure effective data governance and analytics across various teams.

Assist in developing AI solutions for financial planning, working on projects involving data structures, algorithms, and integrating AI features into the platform.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

Lead a team of engineers to evolve the architecture and strategy of the AI Search platform, ensuring high-performance search systems meet strict operational metrics, while nurturing talent and fostering a collaborative culture.

The AI Operations Specialist will support CoinMarketCap's AI team by conducting feature evaluations, developing tools and automations, managing outreach, and collaborating with internal stakeholders to enhance AI operations.

The GTM Engineer will design and build automation systems for lead routing, pipeline management, and data syncing across various tools to enhance sales productivity and revenue growth.

Manage AI/ML projects from initiation to completion, ensuring alignment with goals and standards. Lead cross-functional teams, track project metrics, and oversee stakeholder communication and vendor management.

The role involves managing AI/ML project lifecycles, aligning with IT governance, and leading cross-functional teams to ensure project goals are met within budget and schedule.

Design and operate large-scale GPU infrastructure for distributed AI training, ensuring reliability, performance, and efficient customer partnerships.

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

The Site Reliability Engineer will provision and manage Kubernetes clusters, build automation tools, debug customer issues, and improve infrastructure reliability.

The AI Product Manager will lead product discovery and strategy, prototype solutions using AI tools, perform competitive analysis, track product metrics, advocate for user experience, and collaborate with different teams.

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 role involves reviewing AI-generated outputs, generating content, and ensuring cultural accuracy in various media formats. Attention to detail and analytical skills are essential.

The Backend Developer designs and implements secure APIs, focusing on entitlement enforcement and audit logging, utilizing AI assistance in development.

The Applied AI Researcher will design experiments, train models, and build pipelines for a GenAI platform while contributing to research and deploying systems in production.

Responsible for leading end-to-end AI research projects, developing domain-specific models, mentorship, and optimizing research-to-production processes while collaborating across disciplines.

The Principal Applied AI Researcher will define and lead domain-specific model strategies, manage model lifecycle, mentor researchers, and influence platform decisions in AI research.

The role involves developing and implementing Machine Learning models, managing data pipelines, and supporting Data Science teams with best practices in ML operations and methodologies.

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