Machine Learning Engineer | ML Engineer
ScaleUp Recruitment · Sydney NSW · onsite
USD 150,000 to 220,000 a year
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.
What you will bring
- At least three years taking neural networks from data through training into production or onto real hardware, and 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 your everyday tools.
- Enough C++ (or Rust) to read and work in the code your model runs inside.
- Ownership from prototype to deployment, including fixing it after it shipped, and getting your own data at scale with SQL rather than waiting on someone else.
Nice to have
Making a model meaningfully faster on target hardware and knowing what you gave up for it. Machine learning for autonomous vehicles or robotics. Published work or open source code they can read. Good judgment on which new architectures, transformers and multimodal models included actually apply to the problem.
What is on offer
- Salary in US dollars. Mid-level USD 150,000 to 180,000 base with a 20% target bonus. Senior up to around USD 220,000 base with about 22% bonus, plus equity. Around AUD 220,000 to 320,000 base across the range.
- Relocation covered. Relocation and US immigration costs, corporate housing on arrival, flights for your family and help with a car.
- Leave and benefits. 21 days leave, 10 sick days and 8 public holidays, health premiums paid, a 401(k) with a 4% match, and 20 weeks primary parental leave after a year.
- Work that is judged on what you built. No advanced degree needed and no prior autonomous vehicle experience needed. Shipped systems count far more than credentials.
- A team that ships together. Onsite in Austin, working directly with the planning, infrastructure and vehicle software engineers who take your model's output.
Who can apply
PLEASE NOTE: This role is based in Austin, Texas - on site, relocation & VISA costs all taken care of. Only apply if you are an Australian Citizen and happy to relocate. This is NOT a remote working role. Relocation and US immigration costs are covered.
Apply
ScaleUp Recruitment welcomes applicants from every background however, due to the restrictions around the e3 Visa, you will need to be an Australian Citizen to be eligible for this role.
Apply now, or email sam@scaleuprecruitment.com.au for a confidential chat.