Top AI & Machine Learning Jobs

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Build open-source infrastructure and AI workflows using TypeScript and LLMs to enable high-quality translation and code generation. Collaborate with engineering team, solve difficult product problems, and work onsite in San Francisco.

Design and scale a horizontal AI agent and process millions of government records into agent‑legible knowledge graphs. Build and ship AI-powered features, integrate LLMs into product workflows, and own core backend and frontend production systems.

Conduct exploratory research on LLM agents, reasoning, planning, multi-agent coordination, and evaluation. Design and run experiments, build research prototypes, analyze results, document findings, and collaborate toward publications or open-source contributions under mentorship from research scientists and engineers.

Design and own the decision-intelligence layer: build models and LLM systems to decide which claims to contest and offer amounts, create evaluation pipelines and golden datasets, architect deterministic vs learned components, close feedback loops from outcomes, and produce explainable recommendations for customers.

Lead design and implementation of generative design, computer vision, geometric deep learning, and reinforcement learning systems for automated building design. Integrate AI with BIM tools, deploy production MLOps pipelines, implement physics-informed models, collaborate with architects/engineers, and publish research to advance AEC-focused AI.

Build and ship production-ready generative AI features and autonomous/agentic systems. Architect end-to-end AI services on AWS, integrate AI into a Rails+React product, manage real-estate data pipelines, monitor and optimize model performance and cost, and provide technical leadership and collaboration across teams.

Analyze large structured and unstructured datasets, develop and deploy statistical and machine learning models, build/automate data processing workflows, create visualizations and dashboards, and communicate findings to technical and non-technical stakeholders in support of IC and DoD missions.

Open invitation to propose a role at a fast-moving voice AI startup. Candidates should describe how they'd contribute, be self-starters who have built something notable, and thrive on a small team. Apply with a resume and a short note. On-site in San Francisco (remote depending on role); perks include meals, offsites, and equity.

Own technical engagements end-to-end for large customers: lead technical discovery and POCs, design GPU/HPC cluster and workload architectures, provision and validate production training runs, optimize performance and cost, and build SA assets (runbooks, benchmarks, reference architectures). Act as named technical owner to grow accounts and feed product/engineering with customer feedback.