Machine Learning Engineer | ML Engineer
Machine learning engineer building neural networks for an autonomous vehicle company in Austin, Texas — working on perception, behaviour prediction, and motion planning for self-driving cars and delivery robots, deployed on real hardware. Day-to-day is Python with PyTorch/TensorFlow/JAX plus C++ inference code; Australian citizens only, with relocation and visa costs covered.
- Compensation
- $150K–$220K / yr
- Location
- Sydney NSW
- Work setup
- Onsite
- Seniority
- Middle
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- At least three years taking neural networks from data through training into production or onto real hardware, keeping them working once there
- Real depth in one area: computer vision, or behaviour prediction and motion planning, ideally on vehicles, robots, drones or similar physical systems
- Python and a modern deep learning framework as everyday tools
- Enough C++ (or Rust) to read and work in the code the model runs inside
- Ownership from prototype to deployment, including fixing after ship, and getting own data at scale with SQL
- Must be an Australian Citizen (e3 visa restriction) and happy to relocate to Austin, Texas on-site
Nice to have
- Experience making a model meaningfully faster on target hardware and knowing the trade-offs
- Machine learning for autonomous vehicles or robotics
- Published work or open source code
- Good judgment on which new architectures (transformers, multimodal models) actually apply to the problem
Full description
Salary: $200,000 – $300,000 per year
PLEASE NOTE: This role is based in Austin, Texas (NOT SYDNEY) - on-site, relocation & VISA costs all taken care of.
We are looking for some of Australia's best machine learning engineers ready to make the life-changing decision to relocate to Austin, Texas, where you will join one of the most progressive tech companies in the world. After experiencing rapid growth & funding, this business has working products in a number of US states and will soon be looking at international expansion. Due to this success, they are looking at hiring multiple ML Engineers for their expanding team.
If successful, you will build the neural networks that let self-driving cars and delivery robots see and decide in real traffic.
This transformative opportunity will not only shape your career but also your life experience, as you will get to live and work in one of the most vibrant cities in the world. The business is an autonomous vehicle company that builds two main products:
- Autonomus cars
- Autonomous delivery robots
They are both driverless and can run in real traffic - both vehicle & pedestrian.
They want engineers from Australia, and they are hiring multiple machine learning engineers into their teams covering perception, behaviour prediction, and motion planning. Where you land is settled after the interview process, by what you are strongest at.
To be straight about what this is not: it is not a pipelines and MLOps role. It is neural network work, deployed on real hardware. If your experience is simulation only, or research that never shipped, this one is not the fit.
What you will do
Day-to-day, you work in Python with PyTorch, TensorFlow or JAX. Inference runs in C++ on the vehicle, so you will work inside that code too.
- Perception. Train the models that see, and decide which data they need from a fleet that records far more than any person could review.
- Prediction and planning. Model how pedestrians, cyclists and other drivers are about to move, and turn that into how the car should act.
- Evaluation. Build metrics that track real on-road behaviour, because a model that scores better offline can still drive worse.
- Failure analysis. Dig into rare scenes from real driving logs and feed what you find back into the data and the model.
- Fixed compute. Make hard calls between accuracy, latency and memory on embedded hardware, and defend them.