Senior Machine Learning Engineer

About Anduril Industries

Role Overview

What You’ll Do

• Lead machine learning model design, development, integration, and support for perception and data pipelines across multiple sensor modalities.
• Develop software that automates data management, pipelining, labeling, training, and other machine learning lifecycle activities.
• Manage model selection, training, validation, evaluation, deployment, and regression testing.
• Manage training data sourcing, integration, and quality.
• Develop machine learning tools and processes for classified environments.
• Collaborate with software, mechanical, and systems engineers on system integration and testing.
• Support autonomous vehicle capabilities across design, delivery, operation, and the full product lifecycle.

Required Qualifications

• Bachelor’s degree in Robotics, Mechatronics, Computer Science, Engineering, or a relevant field, or equivalent experience.
• Experience delivering a production-grade software system with a mature machine learning component in a senior role.
• Experience with MLOps, including data acquisition, labeling, data curation, pipeline management, continuous integration, model versioning, and monitoring.
• Ability to define and implement robust validation and verification strategies with data scientists and stakeholders.
• Experience delivering computer vision capabilities across data and model development.
• Ability to work holistically across the software stack and machine learning lifecycle.
• Ability to learn and grow while mentoring junior team members and building team cohesion and capacity.
• Eligibility to obtain and maintain an Australian Government Negative Vetting 2 security clearance.

Preferred Qualifications

• Experience delivering capabilities for a public sector customer.
• Experience with Flyte, Airflow, or Kubeflow workflow management tools.
• Experience with PyTorch, edge machine learning applications, or TensorRT inference engines.
• Experience writing C++, Go, Python, or Rust, plus data management and traceability techniques.
• Interest in progressing toward a Tech Lead Manager role with engineering line-management responsibility.

Compensation and Benefits

• The salary range is an estimate based on compensation factors including experience, education, training, critical skills, and business considerations.
• Full-time offers may include equity grants and comprehensive benefits.