Research Scientist: Post-Training

Generalist • Somerville, MA

21h • $240,000 - $350,000

About The Position

Generalist is building embodied foundation models to help robots intelligently interact with the physical world, with an initial focus on dexterity. The Research Scientist: Post-Training role focuses on turning pretrained robot models into production-ready systems that are useful, controllable, safe, and performant in real-world settings. The work includes fine-tuning, reinforcement learning, steering, human feedback, task specialization, evaluation, and on-robot validation at scale. The role offers the opportunity to develop into a full-stack ML roboticist who can identify and address issues across machine learning, controls, and their intersection.

Requirements

• Experience fine-tuning large models for downstream tasks, such as RLHF, imitation learning, reinforcement learning, distillation, or domain adaptation.
• Experience with embodied AI, robotics, or real-world machine learning systems.
• Care about evaluation, benchmarking, and failure analysis.
• Comfort debugging across the machine learning stack, from loss curves to robot behavior.
• Enjoy rapid iteration with real-world feedback loops.
• Want to bridge the gap between foundation models and physical deployment.

Responsibilities

• Design fine-tuning and adaptation strategies for downstream robotic tasks and embodiments.
• Develop methods to improve reliability, robustness, and controllability.
• Build evaluation frameworks that measure real-world robot performance, not only offline metrics.
• Improve inference-time performance, including latency, stability, and memory footprint, in collaboration with ML infrastructure.
• Leverage techniques such as imitation learning, reinforcement learning, distillation, synthetic data, and curriculum learning.
• Close the loop between model outputs and physical-world outcomes.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed