Top AI & Machine Learning Jobs

Design and run experiments evaluating emerging AI capabilities, build lightweight prototypes, document findings, and influence internal roadmaps. Collaborate with product, platform, and engineering teams to validate AI tooling, identify risks, and transition successful capabilities toward production. The role requires strong software engineering judgment, rapid iteration in ambiguous environments, and hands-on experience with LLMs, agentic systems, evaluation, fine-tuning, RAG, and orchestration frameworks.

Design and run experiments evaluating emerging AI capabilities, build lightweight prototypes, document findings, and communicate risks and recommendations. Collaborate with product, platform, and internal engineering teams to validate AI use cases and transition successful capabilities into production. The role requires rapid iteration in ambiguous environments, strong software engineering judgment, and hands-on experience with LLMs, agentic systems, evaluation, RAG, fine-tuning, and orchestration.

Provide technical leadership and build core components for a scalable AI application platform. Design distributed systems infrastructure, improve performance and reliability, shape architecture and development practices, conduct code reviews, mentor engineers, and lead complex projects from conception through delivery. Collaborate with product, engineering, and design teams to evolve the platform and enhance developer experience.

Build, test, and maintain MongoDB integrations for AI frameworks including LangChain, LangGraph, LlamaIndex, n8n, and Mastra. Own scoped projects from design through release, contribute upstream to open-source repositories, improve CI/CD and compatibility testing, monitor integrations for breaking changes, and collaborate with product, design, and adjacent engineering teams. Develop expertise in AI builder ecosystems, agentic workflows, retrieval, embeddings, and vector search while documenting work and supporting teammates.

Develop and ship production machine learning and statistical algorithms for MongoDB’s core server, query engine, and Atlas platform. The role focuses on resource scaling, release safety, monitoring, automated incident response, and query performance. Responsibilities include prototyping, testing, deployment, model feedback loops, metrics and dashboards, code reviews, and collaboration with engineering teams to deliver measurable business impact.

The Senior Research Scientist will lead research in AI, focusing on large language models and embedding techniques while collaborating with cross-functional teams.

Build and shape AI interfaces that enable developers and AI agents to work with MongoDB, including MCP servers, agent skills, an intelligent assistant platform, and purpose-built agents. Responsibilities include architecture, end-to-end delivery, code reviews, developer experience, incident response through a 24/7 on-call rotation, and mentoring engineers. The role requires independently solving ambiguous problems and collaborating across research, product, design, and engineering teams.

Lead AI-focused marketing strategy and ecosystem to position MongoDB as the default data platform for agentic applications. Own AI narrative, visibility in AI systems, ecosystem integrations and partnerships, documentation and training-data accuracy standards, and acquisition channels for agentic builders. Drive cross-functional alignment and measurable outcomes with product, engineering, and partner teams.

The Staff Research Scientist will conduct AI research, focusing on embedding models and LLMs while collaborating with other scientists and engineers on practical deployments and innovations in information retrieval.

Build and own core AI interface platform components (MCP Server, Agent Skills, Intelligent Assistant Platform). Design, implement, test, and tune scalable backend services, contribute to architecture and developer experience, mentor engineers, and participate in a 24/7 on-call rotation.