Robotics AI Research Scientist — Real-World Systems

Generalist AI; San Mateo (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Generalist is seeking a skilled ML roboticist to advance pretrained robot models into production-ready systems. You will fine-tune large models, apply RLHF/IL, and validate in real-world robotic setups, bridging research and deployment.

You'll collaborate with ML infrastructure and robotics teams to optimize latency, robustness, and controllability while expanding evaluation benchmarks and real-world test suites to ensure dependable performance in physical environments.

Qualifications

• Experience with fine-tuning large models for downstream tasks (RLHF, IL, RL, distillation).
• Background in embodied AI, robotics, or real-world ML systems.
• Strong focus on evaluation, benchmarking and failure analysis.
• Ability to debug across the ML stack from loss curves to robot behavior.
• Enjoy rapid iteration with real-world feedback loops.
• Interest in bridging foundation models and physical deployment.

Responsibilities

• Design fine-tuning and adaptation strategies for downstream robotic tasks.
• Develop methods to improve reliability, robustness, and controllability.
• Build evaluation frameworks measuring real-world robot performance.
• Improve inference-time performance with ML infra collaboration.
• Leverage imitation learning, RL, distillation, synthetic data, curriculum learning.
• Close the loop between model outputs and physical-world outcomes.

Job description

Generalist is seeking a skilled ML roboticist to advance pretrained robot models into production-ready systems. You will fine-tune large models, apply RLHF/IL, and validate in real-world robotic setups, bridging research and deployment.

You'll collaborate with ML infrastructure and robotics teams to optimize latency, robustness, and controllability while expanding evaluation benchmarks and real-world test suites to ensure dependable performance in physical environments.