AI Researcher - Reinforcement Learning

the team iterate on policies faster with standardized benchmarks, automated regression detection, and clear connections between training metrics and field performance Partner with hardware, controls, data, and QA teams to ship RL-trained skills to production customer sites, owning the handoff from research to deployment Key Competencies Sim-to-real practitioner closing the sim-to-real gap on physical systems; understands domain randomization, reward shaping, and the engineering required to make simulated policies transfer reliably to real hardware RL algorithms depth with strong foundation in RL algorithms (PPO, SAC, TD-MPC, or similar); can choose the right approach for the task and modify or extend it when standard methods fall short Full-stack ownership owning data engineering, model architecture, and deployment; treats a promising training curve as the beginning of the job, not the end Effective cross-functional partner working closely with hardware, controls, QA, and data teams to translate RL research into deployed robot skills, and communicates technical constraints clearly across disciplines Minimum

Requirements Strong Python and/or C++ with experience in large codebases and build tools (Bazel or equivalent) Proficiency with PyTorch for RL policy training and experimentation Hands-on experience with simulation platforms (Isaac Sim, MuJoCo, or equivalent) for policy training at scale Demonstrated experience training RL policies for manipulation or locomotion tasks, including addressing the sim-to-real gap on physical hardware Preferred Skills Experience with model-based RL or world-model-guided policy learning that leverages predictive models to improve sample efficiency Familiarity with imitation learning or learning from demonstration (behavior cloning, GAIL, IQL) as a complement or bootstrap to RL Experience deploying RL-trained policies to physical robots in production environments, including monitoring, failure analysis, and iterative improvement Background in legged locomotion, dexterous manipulation, or contact-rich control for physical systems

Compensation Range $200,000 - $300,000 + Equity

Benefits Comprehensive medical, dental, and vision coverage Generous paid time off, company holidays, and parental leave 401(k) plan with company match (100% on the first 3% of contributions, 50% on the next 2%) Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA) options Commuter

benefits (transit and parking) Short-term and long-term disability, and life insurance Employee Assistance Program (EAP) for mental health, financial, and personal support Onsite snacks and catered lunches Equal Opportunity Employer 1X is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, ancestry, citizenship, age, marital status, medical condition, genetic information, disability, military or veteran status, justice system impact, or any other characteristic protected under applicable federal, state, or local law.

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