onsite
Staff Machine Learning/MLOps Engineer - Anduril Industries
MLOps Engineer
Lead end‑to‑end ML system design and deployment, building scalable pipelines on AWS, Docker, and Kubernetes while ensuring robust security and compliance for defense‑grade applications.
About the role
Key Responsibilities
- Architect and implement production‑grade machine learning pipelines from data ingestion to model serving, leveraging AWS services and container orchestration.
- Collaborate with data scientists to translate research prototypes into scalable, maintainable codebases using Python and modern ML frameworks.
- Design and maintain CI/CD workflows for model training, validation, and deployment, ensuring rapid, reliable releases.
- Implement rigorous security controls, audit logging, and compliance checks to meet defense‑grade clearance requirements.
- Mentor junior engineers, conduct code reviews, and promote best practices in MLOps and software engineering.
Requirements
- 10+ years of software engineering experience with a focus on machine learning and MLOps.
- Proficiency in Python, Docker, Kubernetes, and AWS (SageMaker, ECS, EKS, S3).
- Deep understanding of CI/CD pipelines, GitOps, and automated testing for ML workflows.
- Experience with security‑critical environments and familiarity with defense‑grade compliance standards.
- Strong communication skills and ability to lead cross‑functional teams.
Skills
pythonmachine learningmlopsawsdockerkubernetescicd