Senior Machine Learning Engineer

Anduril Anduril · Defense · Sydney, Australia · Maritime & Maneuver Dominance : Undersea Dominance - Engineering & Operations

Senior Machine Learning Engineer to lead the design, development, integration, and support of ML models for perception and data pipelines for autonomous systems in a defense technology company. The role involves managing the ML lifecycle, including data management, training, validation, evaluation, deployment, and regression testing, with a focus on production-grade software systems and MLOps in a classified environment.

What you'd actually do

  1. Lead the design, development, integration and support of machine learning models for perception and data pipelines for a variety of autonomous systems across multiple sensor modalities
  2. Develop software to manage and automate the machine learning lifecycle, including data management, pipelining, labeling and training
  3. Manage model selection, training, validation, evaluation, deployment and regression testing
  4. Manage training data sourcing and integration, and quality
  5. Develop tools and processes for machine learning in a classified environment

Skills

Required

  • Experience in a senior role with the delivery of a production grade software system with a mature machine learning component
  • Experience with the design, implementation and maintenance of ML Operations, including data acquisition, labeling, data curation, pipeline management, continuous integration, model versioning, and monitoring
  • Ability to collaborate with data scientists and stakeholders to define and implement robust validation and verification strategies
  • Experience with the delivery of computer vision capabilities, from the data side as well as the model side
  • Capacity to work holistically on machine learning enabled capabilities up and down the software stack and through lifecycle through design, implementation, operation and sustainment
  • Capacity to learn and grow individually, while mentoring junior team members effectively, building team cohesion and capacity
  • Eligible to obtain and maintain an Australian Government Negative Vetting 2 security clearance (NV2)

Nice to have

  • Experience with the delivery of capability with a public sector customer
  • Experience with workflow management tools such as flyte, airflow, and kubeflow
  • Experience with deep learning frameworks such as PyTorch
  • Experience with edge ML applications
  • Experience with inference engines such as TensorRT
  • Experience writing C++, Go, Python or Rust
  • Proficiency in data management and traceability techniques to maintain high-quality datasets and enable reproducibility of experiments and results
  • Desire to grow in to a Tech-Lead-Manager role, with responsibility for line management of engineers, in addition to delivery

What the JD emphasized

  • delivery of a production grade software system with a mature machine learning component
  • Experience with the delivery of computer vision capabilities
  • Capacity to work holistically on machine learning enabled capabilities up and down the software stack and through lifecycle through design, implementation, operation and sustainment
  • Eligible to obtain and maintain an Australian Government Negative Vetting 2 security clearance (NV2)

Other signals

  • developing un-crewed maritime and air domain systems
  • leverage unsupervised autonomy
  • delivery of long endurance, multi-mission capability
  • entire product life-cycle