Real-World Robotics ML Scientist — Post-Training

Generalist AI; Boston (MA); On-site; USD 180,000 - 260,000; Full time

Job summary

Generalist AI in Boston is seeking a forward-looking ML roboticist to scale pretrained robot models into production-ready systems through fine-tuning, reinforcement learning, steering, human feedback, task specialization, evaluation, and on-robot validation—at scale.

Regardless of your initial background, you will grow into becoming a full-stack ML roboticist capable of quickly pinpoint issues on either side of ML or controls, and all the places in between.

Qualifications

• Experience fine-tuning large models for downstream tasks (RLHF, IL, RL).
• Background in embodied AI, robotics, or real-world ML systems.

Responsibilities

• Design fine-tuning and adaptation strategies for downstream robotic tasks.
• Improve reliability, robustness, and controllability of models.
• Build evaluation frameworks that measure real-world robot performance.
• Improve inference-time performance in collaboration with ML infrastructure.
• Leverage imitation learning, RL, distillation, synthetic data, curriculum learning.
• Close the loop between model outputs and physical-world outcomes.

Skills

Fine-tuning large models

Embodied AI/robotics

Evaluation & benchmarking

ML debugging across stack

Tools

ML infrastructure

Latency optimization

Job description

Generalist AI in Boston is seeking a forward-looking ML roboticist to scale pretrained robot models into production-ready systems through fine-tuning, reinforcement learning, steering, human feedback, task specialization, evaluation, and on-robot validation—at scale.

Regardless of your initial background, you will grow into becoming a full-stack ML roboticist capable of quickly pinpoint issues on either side of ML or controls, and all the places in between.