Senior Machine Learning Engineer, Perception

Anduril Anduril · Defense · Washington, DC · AFS : Discovery Engineering

Senior Machine Learning Engineer focused on perception systems for defense technology. This role involves designing, training, and deploying computer vision and perception models for edge-compatible, mission-critical environments, fusing multi-sensor data, and integrating ML algorithms into production systems. The position also requires developing evaluation frameworks and partnering with cross-functional teams to deliver operational capabilities.

What you'd actually do

  1. Design, train, and deploy computer vision and perception models for edge-compatible, mission-critical environments
  2. Build multi-sensor perception systems that fuse imagery, video, and other sensor data into coherent views of the battlefield
  3. Improve the fidelity, accuracy, and robustness of Lattice's understanding of objects, activities, and environments across varied operational conditions
  4. Integrate state-of-the-art machine learning algorithms into production systems used by customers in real-world scenarios
  5. Develop mission-relevant evaluation frameworks, datasets, and benchmarks to measure perception performance in the field

Skills

Required

  • BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field
  • 5+ years of experience developing computer vision, perception, or machine learning systems in production or advanced research settings
  • Strong experience with deep learning, object detection, and object tracking frameworks
  • Strong programming skills in Python, with the ability to build reliable research and production workflows
  • Strong desire to invent, implement, test, and deploy novel techniques that vastly improve upon state-of-the-art public methods to solve research problem specific to the defense space
  • Experience training, evaluating, and iterating on vision models for detection, tracking, segmentation, classification, or sensor fusion tasks
  • Experience deploying or optimizing ML systems for constrained, real-time, or edge compute environments
  • Ability to work across the full lifecycle of applied ML, from problem formulation and data strategy through deployment and performance monitoring
  • Eligible to obtain and maintain an active U.S. Secret security clearance

Nice to have

  • Advanced degree with a focus on computer vision, perception, robotics, or machine learning
  • Experience with multi-modal or multi-sensor fusion systems
  • Experience deploying deep learning models to embedded, edge, or air-gapped environments
  • Familiarity with real-time perception systems for autonomous platforms, defense applications, or other safety-critical systems
  • Experience building large-scale datasets, labeling pipelines, or benchmarking infrastructure for vision systems
  • Experience working in high-ownership startup environments or defense technology organizations
  • Prior experience with geospatial, ISR, EO/IR, radar, or other battlefield-relevant sensing modalities

What the JD emphasized

  • mission-critical environments
  • real-time
  • edge compute environments
  • real-world scenarios
  • novel techniques that vastly improve upon state-of-the-art public methods to solve research problem specific to the defense space

Other signals

  • deploy computer vision and perception models for edge-compatible, mission-critical environments
  • build multi-sensor perception systems that fuse imagery, video, and other sensor data into coherent views of the battlefield
  • integrate state-of-the-art machine learning algorithms into production systems used by customers in real-world scenarios
  • develop mission-relevant evaluation frameworks, datasets, and benchmarks to measure perception performance in the field