Advanced degree in Robotics, Computer Science, or equivalent industry experience.
Proven track record of deploying AI-enabled hardware solutions in production.
In-depth knowledge of diffusion-based models and optimal control concepts.
Hands-on experience with diffusion policy learning and robust feedback control.
Expertise in integrating various sensors and embedded computing platforms.
Proficient in Python and C++.
Familiar with modern robotics middleware like ROS 2.
Responsibilities
Engage in diffusion-based learning and model deployment.
Focus on optimal control and trajectory optimization.
Integrate hardware and software systems effectively.
Spend 80% of time on hands-on technical work.
Manage project components and team collaboration as needed.
Benefits
Medical, Dental, and Vision Insurance.
Paid Time Off.
401k retirement plan.
Full Job Description
This client is developing solutions for high-throughput logistics using advanced AI, robotics, and real-time hardware integration. They are looking to hire a Physical AI Architect that can go onsite 4 days per week in Boston. In this position, you'll have the opportunity to shape the next generation of physical AI platforms. This role is a blend of technical depth and hands-on building. This is a full time position.
Required Skills & Experience
Advanced degree in Robotics, Computer Science, or similar, or equivalent industry accomplishment
Demonstrated experience bringing AI-enabled hardware solutions into production environments.
Deep knowledge of diffusion-based models for robotics and optimal control concepts
Hands-on expertise with diffusion policy learning, score-based generative modeling, MPC, trajectory optimization, and robust feedback control
Experience integrating sensors (RGB-D cameras, force/torque sensors, encoders), embedded computing (NVIDIA, Jetson, ARM SoCs, FPGAs), and robot actuators
Proficiency with Python and C++
Familiarity with modern robotics middleware (ROS 2 or similar)
What You Will Be Doing Tech Breakdown
40% Diffusion-based learning and model deployment
30% Optimal control, trajectory optimization, and motion planning
30% Hardware-software integration
Daily Responsibilities
80% Hands On
10% Management Duties
10% Team Collaboration
The Offer You will receive the following benefits:
