Senior Research Engineer

Role overview This senior position sits at the intersection of frontier AI research and practical engineering, focused on building large-scale datasets and reinforcement learning environments that improve advanced model capabilities. The work spans synthetic data generation, agentic workflows, post-training, and evaluation across domains like software engineering, finance, retail, and developer tools.

Responsibilities - Investigate capabilities, limitations, and training methods of advanced AI systems, formulating research questions that inform technical strategy. - Design rigorous experiments, prototypes, tooling, and evaluation frameworks for synthetic and agentic data generation, reinforcement learning, and post-training. - Train, test, and evaluate models using modern machine learning tools, drawing evidence-based conclusions from results. - Collaborate across research, engineering, product, and operations teams to translate promising ideas into scalable real-world applications. - Share findings through technical reports, open-source contributions, workshops, or conference participation. - Establish practices for experimental rigor, reproducibility, and data quality across studies.

Requirements - Strong research background with experience in machine learning, AI systems, or related fields. - Proficiency with modern AI and ML tools for training, testing, and evaluating models. - Ability to design experiments, analyze results carefully, and iterate from hypothesis to validated insight. - Strong communication skills for both technical specialists and cross-functional audiences. - Track record of contributing to AI research through publications, open-source work, or equivalent industry experience.

Nice to have - Experience designing RL environments for coding agents, computer-use or browser-use agents, or function-calling agents. - Background building benchmarks or evaluation frameworks for frontier models across long-range, multi-step workflows. - Familiarity with agentic AI design across enterprise and consumer applications.

Benefits and work setup - Compensation range of $250,000 to $350,000 OTE plus equity. - Opportunity to collaborate with leading AI labs and enterprises on post-training and RL environment design. - Potential to publish work at top-tier conferences such as ICLR, ICML, and NeurIPS. - High-autonomy environment emphasizing rapid iteration and meaningful commercial impact.