Perception Engineer, Machine Learning

Anduril Industries is a defense technology company that transforms U.S. and allied military capabilities with advanced technology. We bring the expertise, technology, and business model of 21st‑century innovators to the defense industry, building systems powered by Lattice OS, an AI‑driven operating system that turns data streams into a real‑time, 3‑D command and control center.

We are hiring a Machine Learning Perception Engineer to join our Perception team in Seattle. This hands‑on role focuses on building and deploying production perception systems for autonomous unmanned aerial, surface, and ground vehicles across land, sea, and air. The engineer will own end‑to‑end perception capabilities, from data preparation and model design through deployment, monitoring, and continuous improvement.

• Own perception capabilities end‑to‑end, including detection, classification, segmentation, depth estimation, scene description, tracking, sensor fusion, and calibration across UAV, USV, and UGV platforms.
• Bring state‑of‑the‑art models into production, prototype and integrate research while maintaining deployability and observability in the field.
• Optimize and deploy models to embedded hardware such as NVIDIA Jetson/Orin‑class platforms, meeting 30 ms per frame latency budgets.
• Architect and improve CI/CD pipelines for continuous data ingestion, labeling, training, and deployment.
• Onboard new sensor modalities—e.g., OCR metadata, LiDAR, radar—throughout the pipeline.
• Train models in the cloud and on‑prem, balancing edge and cloud inference workloads.
• Monitor deployed models for performance divergence and build tooling to detect and respond to drift.
• Collaborate with hardware, systems, and program engineers to ship perception capabilities into production systems.

• Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or related field (Master’s preferred).
• 5+ years of industry experience building and deploying perception or computer‑vision systems in production.
• Experience shipping perception software onto real robotic platforms (drones, ground vehicles, marine vehicles, manipulators).
• Strong proficiency in Python for model development with production experience in C++ or Rust for real‑time deployment.
• Hands‑on experience with PyTorch and OpenCV;
  Tensor Flow is welcome.
• Track record of designing, refining, and deploying ML models, ensuring maintainability and field monitoring.
• Expertise in model optimization for embedded inference—quantization, pruning, TensorRT, ONNX.
• Knowledge of classical computer vision: camera calibration, homography, multi‑view geometry, feature‑based methods.
• Experience with structured and unstructured data and integrating new sensor modalities.
• Familiarity with CI/CD practices and writing automated tests for ML pipelines.
• Ownership mindset and cross‑team collaboration skills.
• U.S. Citizen eligible for a U.S. security clearance.

• Master’s or Ph.D. in Computer Vision, Machine Learning, Robotics, or related field.
• Experience with SLAM.
• Experience with AWS training infrastructure, on‑prem GPU clusters, and tools such as Weights & Biases, Flyte, and RunAI.
• Experience with synthetic data generation and sim‑to‑real workflows.
• CUDA / GPU programming expertise.
• Background in defense, aerospace, or autonomous systems.
• Background in robotics perception for drones or marine vehicles.
• Experience with real‑time embedded vision systems.
• Leadership instincts, comfortable mentoring teammates or contributing to architecture and roadmap conversations.
• Publications or contributions to computer‑vision research or open‑source projects.

• Location & work model:
  On‑site in Seattle, WA; occasional travel to events and the Costa Mesa, CA headquarters.
• Employment type:
  
  Full‑time.
• Clearance: U.S. Citizenship required; must be eligible to obtain and maintain a U.S. security clearance.

US salary range: $166,000 – $220,000 USD. The range reflects base salary only; actual offer may vary based on experience, education, and business considerations. Equity grants are included in most full‑time offers. Benefits are comprehensive and available at little to no cost to employees, covering health, recovery, and more.