Robotics ML Scientist: Post-Training & Real-World Impact

Generalist; Somerville (NJ); On-site; USD 150,000 - 210,000; Full time

Job summary

Generalist is seeking a highly capable ML robotics specialist to advance pretrained robot models from research to production. You will tune large models, improve reliability, and build evaluation frameworks that reflect real-world robot performance.

You'll collaborate with ML infrastructure to optimize inference, latency, and memory, while applying RLHF, imitation learning, and distillation to hard robotics tasks. The role blends research rigor with practical deployment.

Qualifications

• 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.

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.

Skills

Fine-tuning

Embodied AI

RLHF

Imitation learning

Evaluation benchmarks

Robotics ML

Job description

Generalist is seeking a highly capable ML robotics specialist to advance pretrained robot models from research to production. You will tune large models, improve reliability, and build evaluation frameworks that reflect real-world robot performance.

You'll collaborate with ML infrastructure to optimize inference, latency, and memory, while applying RLHF, imitation learning, and distillation to hard robotics tasks. The role blends research rigor with practical deployment.