Robotics ML Engineer - Manipulation & Real-World Autonomy

Uncrewed Engineering Jobs; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Uncrewed Engineering Jobs is seeking an ML Engineer, Manipulation, to design learning-based manipulation systems for mobile robots operating in dynamic human environments. You will build perception-to-action models, datasets, evaluation tools, and end-to-end deployment pipelines.

The role requires a BS/MS in robotics or related field, 3+ years of ML robotics experience, and strong PyTorch plus Python skills. Preferred: VLA models, sim-to-real with Isaac Sim/MuJoCo, and edge hardware deployment.

Qualifications

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus).
• 3+ years of experience applying ML to robotics manipulation, visuomotor control, or sequential-to-sequence models.
• Strong proficiency in PyTorch and experience building reliable training/evaluation pipelines.
• Strong Python software engineering and collaboration across ML and robotics teams.

Responsibilities

• Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments).
• Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training.
• Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments.
• Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing.
• Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware.
• Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots.
• Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining.

Skills

ML for robotics

Visuomotor control

Sequential models

Python

Education

Bachelor’s or Master’s degree in Robotics, CS, EE

Tools

PyTorch

TensorRT

ONNX

Isaac Sim

MuJoCo

Job description

Uncrewed Engineering Jobs is seeking an ML Engineer, Manipulation, to design learning-based manipulation systems for mobile robots operating in dynamic human environments. You will build perception-to-action models, datasets, evaluation tools, and end-to-end deployment pipelines.

The role requires a BS/MS in robotics or related field, 3+ years of ML robotics experience, and strong PyTorch plus Python skills. Preferred: VLA models, sim-to-real with Isaac Sim/MuJoCo, and edge hardware deployment.