Senior AI Infrastructure Engineer – Edge & Cloud ML

Anduril; Costa Mesa (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Anduril Industries is seeking a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end ML platform powering its autonomous systems. You will own critical components of ML infrastructure, enabling training, evaluation, hosting, and serving of complex AI models across cloud environments and air-gapped edge devices.

You will collaborate with AI researchers and platform engineers to reduce friction in model development and ensure safe, reliable deployments.

Qualifications

• 5+ years of software engineering experience in production-scale ML infrastructure or distributed systems.
• Proficiency in Python, Go, or C++ with strong systems design knowledge.
• Experience with container orchestration (Docker, Kubernetes) and distributed training frameworks.
• Experience building and maintaining distributed data pipelines for large-scale data.
• Proven track record owning projects end-to-end and ensuring production environments are reliable.
• Eligible to obtain and maintain an active U.S. Top Secret security clearance.

Responsibilities

• Build, scale, and optimize ML infrastructure and tooling for training, evaluation, hosting, and serving models.
• Develop and maintain data pipelines for multi-modal data from physical assets and test sites.
• Implement robust CI/CD pipelines for ML models and safe rollout strategies.
• Collaborate with AI researchers and CV engineers to translate requirements into scalable infra.
• Mentor peers, conduct code reviews, and promote engineering best practices across the team.

Skills

Python

Go

C++

Tools

Docker

Kubernetes

PyTorch Distributed

Ray

Slurm

Megatron-LM

Job description

Anduril Industries is seeking a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end ML platform powering its autonomous systems. You will own critical components of ML infrastructure, enabling training, evaluation, hosting, and serving of complex AI models across cloud environments and air-gapped edge devices.

You will collaborate with AI researchers and platform engineers to reduce friction in model development and ensure safe, reliable deployments.