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Applied Research – Robotics
Prime IntellectPosted 10/19/2026full-timeRemote • California • United States, United KingdomMid-LevelSenior💰 $150,000 - $300,000 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and evaluating embodied AI systems using reinforcement learning, imitation learning, and simulation techniques. Proven ability to manage complex experimental loops and collaborate effectively with research partners while maintaining a strong research agenda.
Highest-signal resume keywords
Reinforcement LearningEmbodied AIPython ProgrammingSimulation DevelopmentAgent Evaluation
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Build environments, evaluations, agent systems, and post-training methods with an external robotics team
- Train and evaluate agents using reinforcement learning, world modeling, imitation learning, planning, and multimodal perception
- Use feedback from simulation and deployed robots
- Test behavior under partial observations, long horizons, changing environments, and hardware and safety constraints
- Build aligned simulation and real-world evaluations for long-horizon embodied tasks
- Combine demonstrations, interventions, offline data, and online feedback into training loops
- Train embodied agents to recover from partial failures, changing scenes, and uncertain states
- Own simulation and real-world environments for training, evaluation, and sim-to-real comparison
- Own long-horizon agents that perceive, plan, act, remember, and recover under hardware constraints
- Develop rewards and evaluations for task success, safety, adaptation, and continual improvement
- Work directly with customers, users, or research partners while maintaining a substantive research agenda
Requirements
What you’ll need- Relevant experience in robotics, embodied AI, RL, imitation learning, control, world models, simulation, computer vision, agent evaluation, or production systems interacting with the physical world
- Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops
- Strong experimental judgment: meaningful baselines, careful trace inspection, clear failure attribution, and willingness to change direction when evidence changes
- Strong Python
- Ability to build artifacts that other researchers and engineers can run, inspect, and extend
- Comfort owning ambiguous problems and keeping partners and teammates current
- Evidence of exceptional work through publications, open-source systems, benchmarks, or shipped products
Benefits
Comp & perks- Equity incentives
- Flexible Work (San Francisco, New York, London, or remote)
- Visa Sponsorship & relocation support
- Professional Development budget
- Team Off-sites & conference attendance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Reinforcement LearningImitation LearningWorld ModelingControl SystemsSimulationComputer VisionAgent EvaluationModel-TrainingExperimental LoopsBehavior Testing
Soft Skills
Experimental JudgmentProblem OwnershipCollaborationAdaptabilityCommunication
Industry Keywords
RoboticsEmbodied AISimulationPhysical InteractionTask Success Evaluation