Staff Research Engineer, Frontier Data

Role overview A Staff Research Engineer role focused on advancing frontier AI systems through rigorous research and practical engineering. The position sits at the intersection of foundational research and applied AI, contributing to large-scale datasets, reinforcement learning environments, and evaluation frameworks that power post-training for leading AI labs and enterprises. Work spans high-value domains such as finance, sales, retail, developer tools, collaboration, and customer experience, with opportunities to publish at top-tier venues.

Responsibilities - Design and run rigorous experiments investigating the capabilities, limitations, and training methods of frontier AI systems. - Develop research-grade datasets, prototypes, tooling, and evaluation frameworks for coding agents, computer-use agents, and function-calling agents. - Train, test, and evaluate models using modern AI and machine learning tools, applying sound practices for reproducibility and data quality. - Translate research findings into improvements for products, platforms, and AI capabilities by collaborating with Engineering, Product, and Operations teams. - Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, and benchmarking. - Share findings through technical reports, publications, open-source contributions, workshops, or conference participation.

Requirements - Strong research background in machine learning, AI systems, or a closely related discipline. - Hands-on experience designing experiments, building prototypes, and evaluating models at scale. - Familiarity with reinforcement learning, post-training techniques, and modern evaluation methodologies. - Ability to translate research into practical, scalable applications with measurable impact. - Excellent communication skills for both specialized and cross-functional audiences. - Track record of contributing to the research community through publications, open-source work, or equivalent outputs.

Nice to have - Experience collaborating across research, engineering, product, and operations teams in a fast-paced environment. - Background applying AI innovations to enterprise workflows or complex multi-step agentic systems.

Benefits and work setup - Compensation range of $250,000 to $400,000 on-target earnings plus equity. - Direct collaboration with leading AI labs and enterprises at the frontier of post-training and RL environment design. - High autonomy, rapid iteration, and meaningful commercial impact within a startup-paced environment. - Opportunities to showcase work at leading conferences such as ICLR, ICML, and NeurIPS. - Commitment to equal opportunity employment and an inclusive, diverse workplace.