Developer Relations Manager, Federal Government

NVIDIA NVIDIA · Semiconductors · DC +2 · Remote

Developer Relations Manager for NVIDIA's Federal Government sector, focusing on autonomous drone systems. The role involves technical engagement with ISVs, primes, and venture-backed companies to promote NVIDIA's accelerated computing stack for edge inference, multi-agent coordination, and synthetic training environments. Requires deep technical credibility in robotics, onboard autonomy, or flight software, with a proven record of influencing partner roadmaps and delivering on DoD timelines.

What you'd actually do

  1. Build and maintain deep technical expertise in autonomous drone mission workloads. These include visual-inertial odometry and SLAM in GPS-denied environments. Also cover multi-modal sensor fusion using EO/IR, SAR, LiDAR, and RF. Include onboard target detection and tracking, swarm and teaming behaviors, and mission-level planning under degraded communications.
  2. Embed with federal autonomy ISVs, drone OEMs, and prime contractors to architect, prototype, and integrate the NVIDIA software stack—Jetson, Holoscan, Isaac ROS, TensorRT, DeepStream, and cuOpt—into flight‑ready autonomy pipelines optimized for SWaP‑constrained airframes.
  3. Lead partner engineering teams through onboarding and integration. Deliver reference architectures, optimized perception and planning pipelines, sample code, and production-grade autonomy workflows. These workflows must be deployable on Group 1–5 platforms.
  4. Observe the autonomy ecosystem to spot new opportunities in collaborative combat aircraft, loitering munitions, counter‑UAS, ISR, and human‑machine teaming. Provide insights to NVIDIA engineering and product teams to guide roadmaps for Jetson Thor, Isaac, and Holoscan.
  5. Engage senior technical leaders—including Chief Architects, CTOs, and autonomy platform leads—across the Aerospace & Defense sector. Tackle sophisticated architectural challenges such as deterministic edge processing, certification‑ready software stacks, and safe autonomy at mission scale.

Skills

Required

  • Bachelor's or Master's (or equivalent experience) in Computer Science, Robotics, Aerospace/Controls, Electrical Engineering, or a related field.
  • 15+ years in the technology industry overall, with 7+ years hands-on in robotics, autonomy, flight software, perception, or edge AI — ideally including time at a defense autonomy company, drone OEM, or an autonomy-heavy program office.
  • Proven technical depth in GPU-accelerated autonomy software: CUDA, TensorRT, Isaac ROS / ROS 2, Holoscan, DeepStream, and on-device model optimization for Jetson-class hardware.
  • Proven experience in architecting real-time perception, sensor fusion, and planning stacks for SWaP-constrained airborne platforms. It includes onboard inference, multi-sensor time synchronization, and mission autonomy when communications are degraded or denied.
  • History of leading developer programs, reference integrations, or ecosystem partnerships with defense ISVs, primes, or venture-backed autonomy companies.
  • Strong ability to translate between engineering depth and senior-executive strategy across program offices, primes, and mission owners.

Nice to have

  • Direct experience shipping autonomy software on a Group 2–5 UAS, a loitering munition, a counter-UAS system, or a coordinated strike aircraft.
  • Background in multi-agent / swarm autonomy, behavior trees, or mission-level AI planners.
  • Experience with synthetic data pipelines, sim-to-real, or digital twin workflows for training and validating perception and policy models.
  • Familiarity with DoD software acquisition pathways, cATO/RMF, and the realities of deploying AI on classified networks and tactical edge hardware.
  • Active clearance (Secret or above) or eligibility to acquire one.

What the JD emphasized

  • U.S. Citizen
  • deep technical credibility in robotics, onboard autonomy, or flight software
  • proven record of influencing partner roadmaps and delivering production autonomy stacks on DoD timelines
  • proven technical depth in GPU-accelerated autonomy software: CUDA, TensorRT, Isaac ROS / ROS 2, Holoscan, DeepStream, and on-device model optimization for Jetson-class hardware
  • proven experience in architecting real-time perception, sensor fusion, and planning stacks for SWaP-constrained airborne platforms. It includes onboard inference, multi-sensor time synchronization, and mission autonomy when communications are degraded or denied.
  • History of leading developer programs, reference integrations, or ecosystem partnerships with defense ISVs, primes, or autonomy companies.

Other signals

  • developer relations
  • federal government
  • autonomous systems
  • edge inference
  • NVIDIA hardware