Lead Engineer – Physical Embodiment of AI

About the Role

At PNNL, our core capabilities are divided among major departments called Directorates, each focused on a specific area of scientific research or function. The National Security Directorate (NSD) drives science-based, mission-focused solutions to address complex, real-world threats. The Physical Detection Systems and Deployment Division, part of NSD, delivers policy-informed technology solutions by removing barriers to real-world implementation. We strive to understand end-user environments to transition technology from development to deployment, providing tools and technologies for combating threats globally.

We are seeking a Lead Engineer to bring automation and autonomy to our R&D, focusing on engineering the physical embodiment of artificial intelligence. This role translates advanced AI/ML algorithms into robust, fieldable autonomous robotic systems, requiring expertise in mechanical engineering, robotics integration, autonomy architectures, and physical/digital test infrastructure development.

This position is based in Richland, WA and requires onsite engagement with robotic laboratories and hardware development environments.

Responsibilities

• Strategic & Technical Leadership
  • Execute the technical vision for AI-enabled autonomous systems with an emphasis on physical system realization and field transition.
  • Lead development of integrated autonomy architectures spanning mechanical systems, sensing, controls, embedded compute, and AI/ML stacks.
  • Translate sponsor mission needs into engineered robotic systems and deployable autonomy capabilities.
  • Establish digital twin and physical prototyping capabilities that accelerate system validation and transition.
• Mechanical Engineering & Robotic System Development
  • Lead mechanical design and integration of robotic platforms, including:
    • Structural systems
    • Actuation and mobility subsystems
    • Power distribution and thermal management
    • Payload integration and sensor mounting architectures
  • Engineer robotic embodiments capable of operating in austere and mission-relevant environments.
  • Develop modular hardware architectures to enable rapid prototyping and mission reconfiguration.
  • Oversee fabrication, assembly, integration, and validation of robotic platforms.
  • Conduct system-level trade studies balancing weight, power, compute, and autonomy performance.
• Autonomy & AI Integration
  • Design and implement end-to-end autonomy stacks integrating:
    • Perception (EO/IR, LiDAR, IMU, multi-modal fusion)
    • State estimation and navigation
    • Planning and decision-making
    • Controls and low-level actuation
  • Deploy advanced ML architectures onto edge and embedded hardware platforms (e.g., NVIDIA Jetson-class devices).
  • Optimize models for real-time, low-latency operation within power- and compute-constrained robotic systems.
  • Develop scalable MLOps pipelines tailored for robotics environments.
• Digital Twin & Test Infrastructure Development
  • Architect and implement high-fidelity digital twin environments for robotic systems using simulation platforms such as Omniverse, Isaac Sim, Unreal, or equivalent.
  • Establish software-in-the-loop (SIL), hardware-in-the-loop (HIL), and human-in-the-loop testing frameworks.
  • Design hybrid physical/digital experimentation workflows linking lab hardware with simulation-based validation.
  • Develop robotic laboratories and autonomy experimentation facilities capable of supporting multi-domain platforms.
  • Build data pipelines for synchronized physical and simulated experimentation.
  • Enable rapid iteration between simulated and real-world deployments.
• Systems Engineering, Test & Evaluation
  • Lead requirements definition, verification, validation, and accreditation (VV&A).
  • Execute Test & Evaluation (T&E) for fieldable systems under sponsor constraints.
  • Conduct performance characterization of mechanical, electrical, and autonomy subsystems.
  • Ensure systems meet safety, cybersecurity, and compliance requirements for defense applications.
  • Lead integration and demonstration efforts during on-site DoD test events.
• Research, Funding & Mentorship
  • Support internal R&D investments in robotic autonomy and physical AI systems.
  • Author and contribute to proposals, journal publications, technical reports, and patent disclosures.
  • Sustain and grow sponsor-funded programs.
  • Mentor junior engineers in mechanical design, robotics integration, and autonomy development.

Requirements

• Minimum Qualifications
  • BS/BA and 7+ years of relevant work experience, or
  • MS/MA and 5+ years of relevant work experience, or
  • PhD with 3+ years of relevant experience.
• Preferred Qualifications
  • Core Technical Depth
    • Demonstrated experience designing and deploying integrated robotic systems.
    • Strong background in mechanical system design for mobile or fieldable platforms.
    • Experience developing and validating digital twins of physical robotic systems.
    • Expertise in autonomy stack integration across hardware and software layers.
    • Experience with embedded systems and edge AI optimization.
    • Proficiency in Python and modern C++.
    • Experience with ROS/ROS2 and robotics middleware.
  • Testbed & Infrastructure Development
    • Experience building robotic laboratories or autonomy experimentation facilities.
    • Experience implementing SIL/HIL frameworks.
    • Experience integrating COTS embedded compute platforms (Jetson, Raspberry Pi, M.2 accelerators).
    • Experience generating and scaling datasets through simulation engines (Omniverse, Isaac Sim, Unreal, Blender).
  • Research & Field Deployment
    • Sustained experience in autonomous systems R&D.
    • Experience transitioning research systems into operational environments.
    • Record of peer-reviewed publications or juried conference presentations.
    • Experience working with federal sponsors, particularly within defense or national security missions.
    • Knowledge of security and compliance requirements for fielded autonomous systems.
• Additional Requirements
  • U.S. Citizenship.
  • Ability to obtain and maintain a federal security clearance. The background investigation includes review of employment, education, financial, and criminal history, as well as interviews with personal references, neighbors, and co-workers.
  • Must demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the Questionnaire for National Security Positions (QNSP).
  • Subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and PNNL Workplace Substance Abuse Program.

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.