Applied Perception Engineering Lead

Applied Intuition Applied Intuition · Robotics · San Diego, CA · Government

Lead a team developing Perception pipelines for defense applications, integrating pre-trained models into real-time systems deployed on hardware. Focus on EO/IR, Radar, and other sensor modalities, with responsibilities for perception autonomy behaviors.

What you'd actually do

  1. Manage a team of talented software engineers working together on exciting perception and perception autonomy projects.
  2. Oversee and contribute to the development of perception pipelines utilizing EO/IR and Radar sensor modalities, with potential of moving into perception pipelines for Acoustics, Passive RF, and Sonar sensors.
  3. Oversee and contribute to the Perception Autonomy service, which includes a growing number of behaviors, such as camera scanning, slew and cue, object following, dynamic EMCON modes, multi-track custody, and track handoff between sensors.
  4. Lead the development and incorporation of pre-trained models (produced by a separate team) into production Perception pipelines.
  5. Ensure your team delivers high quality, robust software that can fulfill project requirements for real-world deployment on hardware components.

Skills

Required

  • MS in computer science, ML, robotics, or related fields
  • 8+ years industry experience in Perception-related fields
  • 2+ years experience in leading teams
  • Experience with deploying software to hardware components with rigorous verification and validation
  • Experience with perception pipelines using real-time data from Radar and EO/IR systems
  • Deep technical understanding of production-level development in C++ and/or Python for integrating object detector, classifier, and few-shot models (ATR models)
  • Experience with designing and working with autonomous systems

Nice to have

  • PhD in a Perception, Robotics, or CS related field
  • Hands-on experience in deploying autonomy in the real world
  • Deep experience in both hardware and software aspects of robotics and sensor systems
  • Competence in signal processing, linear algebra, machine learning, radar, optics, photonics, or electro-optics
  • Active U.S. SECRET clearance preferred

What the JD emphasized

  • integrating pre-trained models
  • production Perception pipelines
  • real-time data from Radar and EO/IR systems
  • deploying software to hardware components

Other signals

  • integrating pre-trained models
  • production Perception pipelines
  • real-time data from Radar and EO/IR systems
  • deploying software to hardware components