Top AI Research Jobs in Seattle, WA

Design and research agentic AI and reinforcement learning systems: build auto-research and coding agents, develop recursive self-improvement and multi-agent frameworks, run RL experiments (RLHF, DPO, PPO), curate training data pipelines, and publish results at top ML venues.

Conduct research developing foundation models for robotics, align text-based reasoning with low-level control policies, design experiments evaluating zero-shot generalization, integrate models into robotic applications with interdisciplinary teams, and present findings at conferences.

The AI Research Engineer will design and implement ML models, develop RL algorithms, and collaborate on integrating ML systems, enhancing AI experimentation.

As a Principal AI Researcher, you will lead advanced AI research in agentic systems and LLMs, shaping research direction, collaborating with engineering teams, and publishing in top-tier venues while fostering a culture of scientific rigor.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Remote contractor role to create and evaluate mathematical problems, proofs, and datasets to train and improve AI models. Assess AI-generated solutions for correctness, produce technical documentation, and collaborate with cross-functional teams to develop benchmark datasets and provide actionable feedback to improve model reasoning.

Perform structured evaluations of AI assistants using MCP and plugins: design realistic prompts, execute multi-step personal workflows (screen-recorded), assess outputs for usefulness and safety, identify failures, and write detailed reports and rubrics. Remote, US-based contractor role requiring 20+ hours/week and rapid task turnaround.

Conduct original research in AI for financial applications, focusing on models, evaluation, and collaboration with engineers to turn ideas into production.

As an AI Research Engineer, you'll design and maintain data pipelines, train models, and work with researchers on innovative solutions.

Lead research and thought leadership on data management and AI readiness, produce actionable insights, advise clients and sales, present at events, mentor analysts, and improve research processes to drive client outcomes.

Lead research on AI integration in manufacturing, develop actionable insights for clients, analyze market trends, and provide expert guidance on digitalization and AI strategies.

Build post-training infrastructure for voice and text agents, including training environments, verifiers, synthetic data pipelines, evaluations, and end-to-end experiments. Select and adapt open-weight models, design robust rewards, deploy models to production, and improve behavior using real-world usage. The role requires strong Python engineering, experience taking models from raw data to production, GPU familiarity, and collaborative remote work.

Join a research and advisory pipeline for an asset-management startup building an auditable reasoning engine. Advise on agentic AI, world models, interpretability, and systemic risk. Help shape research direction, identify failure modes and guardrails, and provide scholarly evidence (papers, GitHub, Google Scholar) and a short written response to demonstrate expertise.