Job Overview
Location
Irvine, California, United States; Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
June 20, 2026
Full Job Description
đź“‹ Description
- • Design and train multi-sensor object detection models for real-time perception on edge compute devices to enhance force protection systems.
- • Develop and maintain core machine learning pipelines for data collection, training, and evaluation across large-scale defense datasets.
- • Deploy deep learning models using TensorRT and ONNX to optimize inference performance on CPU, GPU, and NPU hardware platforms.
- • Optimize on-device vision kernels for latency, memory efficiency, and power consumption in resource-constrained environments.
- • Curate and manage datasets for performance benchmarking, ablation studies, and longitudinal model comparison.
- • Collaborate cross-functionally with camera, systems, and labeling teams to integrate sensor data into Lattice OS’s common operating picture.
- • Own the end-to-end machine learning stack from research and prototyping to production deployment for Counter Intrusion systems.
- • Conduct rigorous experiments and generate highly detailed technical reports to validate model performance and drive iterative improvements.
- • Provide technical mentorship and guidance to junior machine learning engineers on best practices in model development and deployment.
- • Integrate legacy security systems into the Lattice OS ecosystem through scalable, reusable software solutions that avoid bespoke development per customer.
- • Implement and maintain automated continuous integration tests to ensure model reliability and system stability across deployments.
- • Profile and tune ML systems for optimal performance in real-world operational conditions, including field-deployed environments.
- • Apply state-of-the-art techniques in computer vision and autonomous systems to solve complex defense challenges with rapid deployment timelines.
- • Work closely with product, engineering, sales, logistics, and mission success teams to align ML solutions with customer and operational requirements.
🎯 Requirements
- • MS or PhD in Machine Learning, Robotics, or Computer Science with emphasis on Computer Vision
- • BS in Computer Science, Machine Learning, Electrical Engineering, or related field
- • 6+ years of experience developing, benchmarking, and optimizing ML algorithms on large-scale datasets
- • Strong Deep Learning and Computer Vision background
- • Proficiency in C++ development in a Linux environment
- • Experience with Python and deep learning frameworks such as PyTorch, JAX, and TensorFlow
- • Experience deploying models with TensorRT and ONNX
- • Ability to optimize on-device inference and vision kernels across CPU/GPU/NPU
- • Track record of developing and deploying CV models from R&D to production
- • Experience writing and maintaining automated continuous integration tests
- • Knowledge of system profiling and tuning for latency, memory, and power efficiency
- • Ability to conduct experiments, ablation studies, and create highly detailed reports
- • Eligible to obtain and maintain a U.S. Secret security clearance
🏖️ Benefits
- • Salary range of $220,000–$330,000 USD (base only)
- • Highly competitive equity grants included in full-time offers
- • Comprehensive, competitive benefits package available at little to no cost to employees
- • Support for health, recovery, and personal well-being
Skills & Technologies
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About Anduril Industries, Inc.
Anduril Industries is an American defense technology company that develops autonomous systems, sensor networks, and command-and-control software for military and homeland-security applications. Founded in 2017, it designs unmanned aerial vehicles, counter-drone systems, undersea vehicles, and AI-powered surveillance towers, integrating them into a unified operating system called Lattice. The company focuses on rapid hardware-software iteration, open-architecture platforms, and direct contracts with the U.S. Department of Defense and allied governments to address emerging threats across land, sea, air, and cyber domains.
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