Director of AI Engineering & Research, Frontier Systems

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years. ABOUT THE TEAM Frontier Systems is focused on positioning Anduril as a lead provider of specialized hardware and software products for Department of War and Intelligence Community (IC) customers. We work within the DoW and IC to understand their requirements, shape their concepts of operation, and deliver exquisite capability across their problem set. We aim to develop and deploy critically needed capabilities that address our customers’ most pressing national security requirements. ABOUT THE JOB Anduril is seeking a Director of AI Engineering & Research to build and technically lead a world-class machine learning organization spanning deficiency analysis, model development, infrastructure, and deployment onto embedded warfighting compute. In this role, you will set the engineering standards, infrastructure roadmap, and technical focus areas that allow our team to ship safe, secure, and performant agentic and perception systems into the division's programs and products. Own the technical roadmap for agentic and perception capabilities deployed on embedded, often disconnected, warfighting compute — from model architecture choices through quantization, on-device inference, and runtime safety. Set engineering standards and design review processes for ML development across the team: code quality, model evaluation gates, reproducibility, experiment tracking, and release criteria for safety-critical deployments. Drive the ML infrastructure roadmap , including training clusters, data pipelines, evaluation harnesses, model registries, and CI/CD for models targeting classified and air-gapped environments. Collaborate with a variety of internal stakeholders, make build-vs-buy decisions, and prioritize infra investments against capability delivery. Manage and grow a cohort of cleared ML engineers, researchers, and PMs , with a strong emphasis on technical mentorship, hands-on design review, and raising the engineering bar across the org. Provide deep technical leadership on the design, training, and deployment of agents, VLA models, and perception systems — staying close enough to the work to debug architectures, provide direction, and unblock hard technical problems. Architect the data flywheel on top of the world's largest defense robotics dataset: ingestion, curation, labeling, and training pipelines that scale with fleet growth. Partner with internal T&E teams to define rigorous, defense-specific evaluation benchmarks and codify them into automated regression suites that gate releases. Collaborate with US-based Frontier AI Labs on technical integrations that bring frontier capabilities onto embedded hardware. REQUIRED QUALIFICATIONS Experience managing and growing ML engineering teams, with a track record of setting technical standards and review processes that scaled with the org. Hands-on experience shipping ML systems into production, including into classified, disconnected, or air-gapped environments. Deep expertise in modern deep learning and generative AI: agents, VLA models, multimodal perception, and the training/fine-tuning stacks behind them. Demonstrated ownership of ML infrastructure — training pipelines, distributed training, eval infrastructure, or on-device inference runtimes. Strong programming skills and willingness to remain technically hands-on in design, code review, and debugging. Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance. PREFERRED QUALIFICATIONS Experience with edge-deployed ML systems, including model compression, quantization, and inference optimization on constrained compute. Experience designing evaluation frameworks and benchmarks for safety-critical or adversarial domains. Prior work in Defense Tech and/or startups. Active U.S. Top Secret SCI security clearance. US Salary Range $335,000 — $444,000 USD The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Andur