Senior AI Infrastructure Engineer

The role

You will build, scale, and optimize the end-to-end machine learning platform that powers autonomous systems. This includes owning ML platform components and MLOps tooling to train, evaluate, host, and serve complex AI models.

What you will do

• Build, optimize, and maintain scalable training, orchestration, and experimentation infrastructure.
• Identify and resolve bottlenecks in the ML lifecycle through tooling for experiment tracking, profiling, and hyperparameter tuning.
• Implement and scale robust data pipelines to process multi-modal data.
• Deploy high-throughput, low-latency model serving frameworks for cloud and air-gapped tactical edge hardware.
• Develop robust CI/CD pipelines for ML models.
• Implement pipelines for model evaluation, validation, and reinforcement learning alignment loops.
• Partner with AI Researchers and Computer Vision engineers to translate modeling requirements into infrastructure.
• Mentor peers, conduct design and code reviews, and champion engineering best practices.

Required qualifications

• 5+ years of software engineering experience with success in building and operating production-scale machine learning infrastructure or distributed systems.
• Proficiency in Python, Go, or C++.
• Strong grasp of software engineering fundamentals, systems design, and concurrent programming.
• Hands-on experience with container orchestration (Docker, Kubernetes).
• Hands-on experience with 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.

Nice to have

• 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.

Benefits

• Comprehensive, competitive benefits package available at little to no cost to employees.

Before you apply

• Eligible to obtain and maintain an active U.S. Top Secret security clearance.
• 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.

About the company

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. Their family of systems is powered by Lattice OS, an AI-powered operating system.