Senior Machine Learning Engineer
Salary not listed • Sydney, New South Wales, Australia • Full-time
Posted 9mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Sydney, New South Wales, Australia
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Anduril Australia is developing un-crewed maritime and air domain systems that leverage unsupervised autonomy for long endurance, multi-mission capability. This Senior Machine Learning Engineer role is crucial for projects like the Extra Large Autonomous Undersea Vehicle (XL-AUV) Program, requiring deep experience in developing, testing, validating, and deploying machine-learning based sensor processing and the associated technical toolchains. The engineer will architect, design, deliver, support, and evolve next-generation autonomous vehicles throughout their product lifecycle, contributing to Anduril's mission of transforming defense capabilities with advanced technology.
Responsibilities
- Lead the design, development, integration, and support of machine learning models for perception and data pipelines for autonomous systems across multiple sensor modalities.
- Develop software to manage and automate the machine learning lifecycle, including data management, pipelining, labeling, and training.
- Manage model selection, training, validation, evaluation, deployment, and regression testing.
- Manage training data sourcing, integration, and quality.
- Develop tools and processes for machine learning in a classified environment.
- Collaborate with cross-functional teams (software, mechanical, systems engineers) to ensure effective system integration and testing.
Requirements
- Bachelor’s degree in Robotics, Mechatronics, Computer Science, Engineering, a relevant field, or equivalent experience.
- Experience in a senior role delivering a production-grade software system with a mature machine learning component.
- Experience with the design, implementation, and maintenance of ML Operations (data acquisition, labeling, curation, pipeline management, CI, model versioning, monitoring).
- Ability to collaborate with data scientists and stakeholders to define and implement robust validation and verification strategies.
- Experience delivering computer vision capabilities, both from a data and model perspective.
- Capacity to work holistically on ML-enabled capabilities across the software stack and lifecycle (design, implementation, operation, sustainment).
- Capacity to learn and grow individually, while mentoring junior team members.
- Eligible to obtain and maintain an Australian Government Negative Vetting 2 security clearance (NV2).
Benefits
- Highly competitive equity grants
- Top-tier benefits (health, recovery, etc.)