Top AI & Machine Learning Jobs

Early-career engineer to develop and integrate Python components for AI use cases. Support data preparation, model integration, RAG pipelines, embeddings, and vector retrieval. Work with Senior AI Engineers on testing, debugging, documentation, deployment, and applying cloud and software engineering best practices.

Develop and integrate Python components for AI use cases, support data preparation, model integration, RAG pipelines and API consumption, and assist testing, debugging, documentation, and deployment under senior mentorship.

Lead Data Scientist responsible for developing and implementing AI and ML solutions to support marketing and business engagement. The role involves technical leadership, model development, data analysis, stakeholder collaboration, and ensuring compliance with governance standards.

The VP, AI Innovation leads AI strategy at MetLife, focusing on cutting-edge applications of AI to enhance customer experiences and operational efficiency. Responsibilities include market intelligence, applied AI leadership, cross-functional collaboration, and establishing best practices for responsible AI deployment.

Assist in designing, developing, and testing AI agents and workflows, focusing on Python-based backend components, integration, and collaboration with senior engineers.

Oversee development of AI solutions, including LLM workflows, ensuring alignment with business needs, quality standards, and governance.

Design and build enterprise AI agents, multi-agent systems, and AI-enabled applications. Implement microservices-based architectures, APIs, and integrations with backend systems and data platforms. Build production ML/NLP solutions (document processing, RAG, vector DBs), manage data pipelines, and use Azure DevOps/CI-CD for deployment and production support.

The role focuses on adopting AI tools by measuring platform usage, creating training programs, and enhancing user engagement across MetLife's operations.

The Enterprise AI Platform Operations Engineer leads the operations of AI productivity platforms, managing incident response, compliance, and automation solutions while ensuring effective platform governance across the organization.

Define and advance data and platform architecture for Performance & Platform Management. Establish scalable patterns for data, AI, and API integrations; integrate AI/ML insights into operational workflows; partner with product, engineering, and business stakeholders; support SDLC and governance to ensure performance optimization, measurement foundations, and enterprise visibility.