Staff AI Infrastructure Engineer: Scale ML at the Edge

Anduril Industries; Costa Mesa (CA); On-site; USD 220,000 - 292,000; Full time

Job summary

Anduril Industries is seeking a Staff AI Infrastructure Engineer to architect and scale the end-to-end ML platform powering autonomous systems. You will own the technical roadmap, build robust ML tooling, and manage data from terabytes of sensors and simulations in cloud and air-gapped environments.

You will lead the infrastructure engineering team over time, mentoring engineers while partnering with AI researchers and platform teams to raise experimentation velocity and system reliability.

Qualifications

• 7+ years of software engineering experience designing, building, and operating production-scale ML systems.
• Proficient in Python, Go, C++, or similar backend languages.
• Deep experience with containerized deployments (Docker, Kubernetes), GPU scheduling, and distributed training frameworks.

Responsibilities

• Architect the ML Platform: design, build, and maintain our training, orchestration, and experimentation infrastructure to support state-of-the-art model development.
• Optimize AI Researcher Velocity: identify bottlenecks and build automated tools for hyperparameter tuning, model profiling, and experimentation tracking.
• Build Data Pipelines at Scale: design and scale robust ETL pipelines for terabytes of multi-modal data.
• Deploy Model Serving Infrastructure: architect high-throughput serving frameworks for cloud and edge environments, with CI/CD for ML models.
• Implement Evaluation & Alignment Loops: automated pipelines for evaluation, validation, and RLHF/DPO to ensure safety and predictability.
• Collaborate and Pioneer: work with AI Researchers, Computer Vision teams, and platform engineers to standardize infrastructure across autonomous programs.

Skills

Python

Go

C++

ML systems design

Docker

Kubernetes

MLOps

Leadership

ETL pipelines

GPU orchestration

Tools

PyTorch Distributed

Ray

Slurm

Megatron-LM

Job description

Anduril Industries is seeking a Staff AI Infrastructure Engineer to architect and scale the end-to-end ML platform powering autonomous systems. You will own the technical roadmap, build robust ML tooling, and manage data from terabytes of sensors and simulations in cloud and air-gapped environments.

You will lead the infrastructure engineering team over time, mentoring engineers while partnering with AI researchers and platform teams to raise experimentation velocity and system reliability.