Top AI & Machine Learning Jobs

Lead MongoDB's strategy to increase LLM and answer-engine visibility by optimizing content, structured data, and community signals. Build and scale an AEO/SEO team, implement technical information architecture (JSON-LD, knowledge graphs, RAG-friendly docs), coordinate UGC/community advocacy, evangelize AI-first content practices, and develop analytics/attribution (Share of Model, citation impact) to drive PLG acquisition.

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.

Build and maintain agent skills and the platform for authoring, evaluating, publishing, and monitoring them. Implement CLIs, libraries, CI integrations, evaluation harnesses, metrics, and safety/quality gates. Investigate failures, design datasets and workflows, and collaborate with cross-functional teams to improve agent behavior and automation reliability.

Build and maintain agent skills, tooling, and evaluation infrastructure: CLIs, libraries, CI workflows, metrics, safety gates, and observability for agent behavior. Design evaluation datasets, investigate failures, and collaborate with product and security teams to ship reliable, reusable internal systems.

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.

Build systems, tooling, and deployment workflows to package, validate, and deliver Voyage embedding models across cloud providers and third-party environments. Improve model server performance, ensure deployment correctness and observability, debug cross-stack issues, and collaborate with model-serving teams and external partners for reliable production deployments.