Research Engineer (Reinforcement Learning)

Location: Remote or in-person at offices in San Francisco, United States

Salary: $150,000–$350,000 annual cash compensation, including equity incentives

Company

hirify.global is building an open superintelligence stack that combines compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for frontier AI research.

What you will do

• Develop and test reinforcement learning methods for reasoning, coding, and long-horizon tasks.
• Investigate stability in asynchronous reinforcement learning, including policy staleness, trainer-sampler mismatch, and numerical differences between training and rollouts.
• Design scaling experiments to study the effects of model size, training compute, and task horizon on learning dynamics.
• Use controlled ablations and evaluations to distinguish learning gains from reward exploitation, evaluation artifacts, and training bugs.
• Extend prime-rl to support new algorithms, models, and asynchronous training workflows.
• Build diagnostics and improve performance and numerical correctness across trainers, rollout workers, and environments.

Requirements

• Demonstrated depth in at least one of reinforcement learning algorithms, empirical research on model training, or distributed machine learning systems.
• Strong programming skills in Python and experience with PyTorch or a comparable machine learning framework.
• Ability to design controlled experiments, interpret results, and debug unexpected model or system behavior.
• Experience taking a research idea or systems change through implementation, testing, and evaluation.
• Ability to work remotely or in person at the San Francisco offices.

Nice to have

• Experience with distributed training frameworks or asynchronous rollout pipelines.
• Experience diagnosing unstable reinforcement learning runs, including policy-staleness or numerical issues.
• Experience with coding agents, verifiable rewards, or long-horizon environments.

Culture & Benefits

• Visa sponsorship and relocation assistance are available for international candidates.
• Flexible remote and in-person work arrangements.
• Quarterly team off-sites, hackathons, conferences, and learning opportunities.
• Work with a mission-driven team focused on accelerating science and AI.