Robot Learning Engineer: Scalable Multimodal Policies

Proception Inc.; Palo Alto (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Proception Inc. in Palo Alto is seeking a Robot Learning Researcher/Engineer to advance imitation learning, foundation models, and reinforcement learning for general-purpose control policies.

You will design scalable training pipelines and build the data engine behind the models for large-scale, multimodal tasks. You will train multimodal policies and push them to state-of-the-art performance on real robots, collaborating with AI, hardware and perception teams to deliver production-quality

Qualifications

• MS or PhD in Robotics, Computer Science, ML or related field (or equivalent).
• Proven track record training neural networks end-to-end with reproducible results.
• Experience developing robot learning policies (diffusion, 3D, V-L-A, or video action).
• Experience training models at scale with multi-GPU/multi-node setups and large datasets.
• Strong software engineering in Python and PyTorch or JAX; Linux environment; C++ a plus.
• Experience building large-scale data pipelines for robot learning (demo collection, curation, filtering).
• Comfort with high-dimensional actions and multimodal observations.
• Rigorous evaluation: benchmarks, ablations, robust conclusions.
• Hands-on robotics experience with hardware bring-up, teleoperation, data collection.
• Experience with high-performance simulation (MuJoCo, Isaac Gym/Lab) and sim2real.
• Familiarity with contact-rich/dexterous manipulation, tactile sensing, or differentiable sim

Responsibilities

• Design scalable training pipelines for general-purpose manipulation policies.
• Train large multimodal policies and push them to state-of-the-art on real tasks.
• Build data engine behind the models: demonstration collection, curation and dataset design at scale.
• Integrate visual, proprioceptive, and tactile feedback into policy architectures.
• Take policies from training runs to real hardware with on-robot deployment.
• Collaborate across AI, hardware and perception teams to build closed-loop systems.
• Publish or contribute to research while delivering production-grade control stacks.

Skills

Imitation Learning

Foundation Models

Reinforcement Learning

Multimodal Models

Diffusion Policies

3D Policies

Video Action Models

Large-scale Training

Python

PyTorch

JAX

Education

MS or PhD in Robotics, Computer Science, Machine Learning, or related field

Tools

Python

PyTorch

JAX

C++

Job description

Proception Inc. in Palo Alto is seeking a Robot Learning Researcher/Engineer to advance imitation learning, foundation models, and reinforcement learning for general-purpose control policies.

You will design scalable training pipelines and build the data engine behind the models for large-scale, multimodal tasks. You will train multimodal policies and push them to state-of-the-art performance on real robots, collaborating with AI, hardware and perception teams to deliver production-quality