Physical AI Architect: Diffusion & Control for Robotics

Pickle Robot Company; Boston (MA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Unlimited vacation

Paid holidays

401(k) contributions

Travel expenses covered

Job summary

Pickle Robot Company is seeking a senior robotics architect to own the end-to-end design of the Physical AI stack deployed on production hardware. You will lead diffusion-based policy learning and advanced control techniques for reliable robot picking and unloading tasks, shaping the autonomy roadmap with cross-functional teams.

You will mentor engineers, integrate sensors, compute, and actuators, and push performance while maintaining maintainability and observability.

Qualifications

• MS or PhD in Robotics, CS, or equivalent demonstrated expertise.
• Deep diffusion models expertise for robot learning.
• Strong command of MPC and trajectory optimization.
• Hands-on hardware integration with sensors and compute.
• Proficiency in Python and C++ with ROS 2 familiarity.
• Experience deploying AI-powered systems to production.
• Excellent communication for cross-functional decisions.

Responsibilities

• Serve as the technical architect for Pickle Robot's Physical AI stack.
• Lead diffusion-based policy learning and optimal control techniques.
• Define the technical roadmap for diffusion models and MPC integration.
• Drive hardware integration across sensors, compute, and actuators.
• Identify and resolve performance bottlenecks at model, motion, and hardware levels.
• Mentor senior engineers and grow the autonomy team's depth.

Skills

AI systems deployment

Diffusion models

Optimal control (MPC)

Python

C++

ROS 2

Hardware integration

Systems architecture

Cross-functional leadership

Communication skills

Education

MS or PhD in Robotics or CS

Equivalent demonstrated expertise

Tools

NVIDIA Jetson

ARM SoCs

FPGAs

ROS 2 middleware

Job description

Pickle Robot Company is seeking a senior robotics architect to own the end-to-end design of the Physical AI stack deployed on production hardware. You will lead diffusion-based policy learning and advanced control techniques for reliable robot picking and unloading tasks, shaping the autonomy roadmap with cross-functional teams.

You will mentor engineers, integrate sensors, compute, and actuators, and push performance while maintaining maintainability and observability.