Senior Research Engineer, Frontier Data

Role overview

A senior research engineering position focused on advancing frontier AI systems through large-scale datasets, reinforcement learning (RL) environments, and evaluation frameworks used to post-train leading models. The role sits at the intersection of applied research and engineering, translating experimental findings into scalable improvements for software-engineering agents, computer-use or browser-use agents, and MCP-based function-calling systems. Work spans synthetic and agentic data generation, model understanding, benchmark design, and rigorous experimentation across high-value domains.

Responsibilities

- Formulate and investigate research questions about frontier model capabilities, limitations, and training methods - Design and run rigorous experiments, drawing evidence-based conclusions and iterating quickly from hypothesis to validated insight - Build research-grade datasets, prototypes, tooling, and evaluation frameworks for coding, UI, and function-calling environments - Partner with research, engineering, product, and operations teams to move promising ideas into scalable production systems - Contribute to the broader research community through technical reports, publications, open-source work, or conference participation where appropriate

Requirements

- Strong background in machine learning research, including experimental design and statistical analysis - Hands-on experience training, testing, and evaluating models using modern AI tooling - Ability to translate research findings into product, platform, or capability improvements - Commitment to reproducibility, data quality, and sound interpretation of experimental results - Comfort collaborating across research, engineering, product, and operations functions

Nice to have

- Publications or submissions to venues such as ICLR, ICML, or NeurIPS - Experience with reinforcement learning environments, synthetic data generation, or post-training techniques - Familiarity with agentic systems, developer tools, or enterprise workflow automation

Benefits and work setup

- Compensation range of $250,000 to $350,000 OTE plus equity - Opportunity to contribute work shared at top AI research conferences - High-autonomy setting with rapid iteration and direct impact on production AI systems