Physical AI Architect
Pickle Robot Company
full-time
Posted on:
Location Type: Hybrid
Location: Charlestown • Massachusetts • United States
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Tech Stack
About the role
- Serve as the technical architect for Pickle Robot's Physical AI stack, owning the end-to-end design of perception, planning, and control systems deployed on production hardware.
- Lead the application of diffusion-based policy learning and optimal control techniques to robot manipulation and picking tasks, with a focus on real-world reliability and cycle time performance.
- Drive hardware integration efforts across sensors, compute, and actuators — ensuring AI systems are co-designed with the physical platform from the ground up.
- Define the technical roadmap for how diffusion models and optimal control complement each other in Pickle Robot's autonomy architecture, and build internal alignment around that vision.
- Partner with firmware, mechanical, and software engineering teams to ensure AI design decisions are grounded in hardware constraints and operational realities.
- Identify and resolve performance bottlenecks at the intersection of model inference, motion execution, and hardware throughput.
- Mentor senior engineers and help grow the technical depth of the broader autonomy team.
Requirements
- Demonstrated track record of shipping AI-powered systems to production — we want to hear about systems you have deployed, not just prototyped.
- MS, or PhD in Robotics, Computer Science or a related field, or equivalent demonstrated expertise through shipped products.
- Deep subject matter expertise in diffusion models applied to robot learning (e.g., diffusion policies, score-based generative models for behavior cloning or planning).
- Strong command of optimal control theory and practice, including model predictive control (MPC), trajectory optimization, and feedback control design for physical systems.
- Practical understanding of how diffusion-based learning and optimal control approaches are complementary — and the architectural judgment to combine them effectively.
- Hands-on experience with hardware integration: sensor pipelines (RGB-D, force/torque, encoders), embedded compute (NVIDIA Jetson, ARM SoCs, FPGAs), and actuator interfaces.
- Proficiency in Python and C++; familiarity with ROS 2 or equivalent robotics middleware.
- Experience with real-time systems constraints and the performance tradeoffs inherent in deploying learned models on robot hardware.
- Strong systems-level thinking — you design for maintainability, observability, and failure modes, not just peak performance.
- Excellent communication skills and the ability to drive technical decisions across cross-functional teams.
- Willing to work in the office from our Charlestown, MA location at least three days per week.
Benefits
- health, dental, & vision insurance
- unlimited vacation, along with all federal and state holidays
- 401K contributions of 5% your salary
- travel supplies
- other items to make your working life more fun, comfortable, and productive.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
diffusion modelsoptimal control theorymodel predictive controltrajectory optimizationfeedback control designhardware integrationsensor pipelinesembedded computePythonC++
Soft Skills
mentoringcommunicationsystems-level thinkingcross-functional collaboration
Certifications
MS in RoboticsPhD in Computer Science