Staff Research Engineer, Enterprise Knowledge

Role overview This position sits at the intersection of research and engineering, building large-scale datasets and reinforcement learning environments that power post-training for leading AI labs and enterprises. The environments evaluate and improve models on complex, multi-step workflows in high-value domains such as finance, sales, retail, developer tools, collaboration, and customer experience. Researchers investigate high-impact questions on synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation.

Responsibilities - Investigate the capabilities, limitations, and training methods of frontier AI systems and formulate research questions that shape product and platform strategy. - Design and run rigorous experiments, building research-grade datasets, prototypes, tooling, and evaluation frameworks. - Train, test, and evaluate models using modern AI and machine learning tools, and draw clear, evidence-based conclusions from results. - Translate research findings into improvements for products, platforms, and AI capabilities by collaborating with Research, Engineering, Product, and Operations teams. - Build environments for software engineering and coding agents, UI environments for computer-use and browser-use agents, and MCP-based environments for general function-calling agents. - Share findings through technical reports, publications, open-source work, workshops, or conference participation.

Requirements - Strong research background with experience formulating and executing original research in machine learning, AI, or a closely related technical field. - Solid engineering skills to build research-grade prototypes, tooling, and evaluation frameworks. - Deep understanding of modern large language models, reinforcement learning, post-training techniques, and the frontier AI research landscape. - Excellent experimental design, quantitative analysis, and cross-functional communication skills.

Benefits and work setup - Compensation range of $250,000 to $400,000 OTE plus equity. - Opportunity to publish at leading conferences such as ICLR, ICML, and NeurIPS. - High autonomy, rapid iteration, and direct collaboration with leading AI labs and enterprises on high-value post-training and RL environment design.