Job description

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 The Air Dominance & Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers. We are looking for software engineers and roboticists excited about creating a powerful autonomy software stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications. ABOUT THE JOB We are looking for a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end machine learning platform that powers Anduril’s autonomous systems. In this role, you will own critical components of our ML platform and MLOps tooling. You will build and operate the infrastructure required to train, evaluate, host, and serve complex AI models (including LLMs, computer vision, and RL agents) across cloud environments and air-gapped, edge-deployed networks. Working closely with AI Research Scientists and Platform Engineers, you will eliminate friction in model development, optimize hardware utilization, and ensure robust delivery of models into safety-critical operational environments. WHAT YOU’LL DO Build, optimize, and maintain scalable training, orchestration, and experimentation infrastructure to accelerate state-of-the-art model development. Identify and resolve bottlenecks in the ML lifecycle by developing tooling for experiment tracking, automated profiling, and hyperparameter tuning. Implement and scale robust data pipelines (ETL) to process multi-modal data (video feeds, radar, flight telemetry, and simulation logs) captured from physical assets and test sites. Deploy high-throughput, low-latency model serving frameworks optimized for both cloud environments and resource-constrained, air-gapped tactical edge hardware. Develop robust CI/CD pipelines for ML models, including automated regression testing, validation benchmarks, and safe rollout/rollback strategies. Implement pipelines for model evaluation, validation, and reinforcement learning alignment loops (RLHF/DPO) to ensure predictability and safety in mission-critical deployments. Partner with AI Researchers and Computer Vision engineers to translate modeling requirements into scalable, reusable infrastructure. Mentor peers, conduct thorough design and code reviews, and champion engineering best practices across the team. REQUIRED QUALIFICATIONS 5+ years of software engineering experience with demonstrated success in building and operating production-scale machine learning infrastructure or distributed systems. Proficiency in Python, Go, or C++, with a strong grasp of software engineering fundamentals, systems design, and concurrent programming. Hands-on experience with container orchestration (Docker, Kubernetes) and distributed training frameworks (e.g., PyTorch Distributed, Ray, Slurm, or Megatron-LM). Experience building and maintaining distributed data pipelines handling large-scale unstructured or multi-modal datasets. Track record of owning projects end-to-end—from technical design to production deployment and operational monitoring. Eligible to obtain and maintain an active U.S. Top Secret security clearance. PREFERRED QUALIFICATIONS Experience deploying ML infrastructure, model serving, or artifacts in secure, air-gapped, or regulated environments (e.g., IL5/IL6, GovCloud). Hands-on experience profiling GPU/accelerator workloads, resolving hardware/network bottlenecks, and optimizing compute utilization. Experience supporting workloads for Large Language Models, Generative AI, or Reinforcement Learning (RL) pipelines. Experience with multi-tenant cluster management, including fair scheduling, GPU slicing, and quota enforcement. Familiarity with production ML observability frameworks, including data drift detection and automated evaluation pipelines. US Salary Range $191,000 — $253,000 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 Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including: Benefits At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits . Protecting Yourself from Recruitment Scams Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information. To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind: No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates. Please always verify communications: Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address. Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links. What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to contact@anduril.com . Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts. Data Privacy To view Anduril's candidate data privacy policy, please visit anduril.com . By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.

Requirements

Must-haves

We are looking for a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end machine learning platform that powers Anduril’s autonomous systems.
Build, optimize, and maintain scalable training, orchestration, and experimentation infrastructure to accelerate state-of-the-art model development.
Identify and resolve bottlenecks in the ML lifecycle by developing tooling for experiment tracking, automated profiling, and hyperparameter tuning.
Implement and scale robust data pipelines (ETL) to process multi-modal data (video feeds, radar, flight telemetry, and simulation logs) captured from physical assets and test sites.
Deploy high-throughput, low-latency model serving frameworks optimized for both cloud environments and resource-constrained, air-gapped tactical edge hardware.
Develop robust CI/CD pipelines for ML models, including automated regression testing, validation benchmarks, and safe rollout/rollback strategies.
Implement pipelines for model evaluation, validation, and reinforcement learning alignment loops (RLHF/DPO) to ensure predictability and safety in mission-critical deployments.
Partner with AI Researchers and Computer Vision engineers to translate modeling requirements into scalable, reusable infrastructure.
Mentor peers, conduct thorough design and code reviews, and champion engineering best practices across the team.
5+ years of software engineering experience with demonstrated success in building and operating production-scale machine learning infrastructure or distributed systems.
Proficiency in Python, Go, or C++, with a strong grasp of software engineering fundamentals, systems design, and concurrent programming.
Hands-on experience with container orchestration (Docker, Kubernetes) and distributed training frameworks (e.g., PyTorch Distributed, Ray, Slurm, or Megatron-LM).
Experience building and maintaining distributed data pipelines handling large-scale unstructured or multi-modal datasets.
Track record of owning projects end-to-end—from technical design to production deployment and operational monitoring.
Eligible to obtain and maintain an active U.S. Top Secret security clearance.
Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.

Nice-to-haves

Experience deploying ML infrastructure, model serving, or artifacts in secure, air-gapped, or regulated environments (e.g., IL5/IL6, GovCloud).
Hands-on experience profiling GPU/accelerator workloads, resolving hardware/network bottlenecks, and optimizing compute utilization.
Experience supporting workloads for Large Language Models, Generative AI, or Reinforcement Learning (RL) pipelines.
Experience with multi-tenant cluster management, including fair scheduling, GPU slicing, and quota enforcement.
Familiarity with production ML observability frameworks, including data drift detection and automated evaluation pipelines.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlci/cdpythongodockerkubernetes

Platform: greenhouse
Effort: quick

Benefits

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