Research Scientist: Post-Training

Job description

We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.

The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs.

At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone.

Job responsibilities

Designing fine-tuning and adaptation strategies for downstream robotic tasks and embodiments
Developing methods for improving reliability, robustness, and controllability
Building evaluation frameworks that measure real-world robot performance, not just offline metrics
Improving inference-time performance (latency, stability, memory footprint) in collaboration with ML infrastructure
Leveraging techniques such as imitation learning, RL, distillation, synthetic data, and curriculum learning
Closing the loop between model outputs and physical-world outcomes
Have experience with fine-tuning large models for downstream tasks (RLHF, IL, RL, distillation, domain adaptation, etc.)
Have worked on embodied AI, robotics, or real-world ML systems

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Research Scientist: Post-Training

Job description

Job responsibilities

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