Job Description

Not so long ago, in a startup not so far away… a new signal was detected.

In a world where machines follow pre-programmed rules and struggle with the unexpected, a team of rebels is engineering a new future.

Their mission?

To create intelligent systems that don’t just follow commands - but learn, adapt, and make decisions on their own.

The challenge?

The brains behind the operation - the AI models that power perception, planning, and control - are still evolving.

Without them, autonomy remains just a dream.

To complete this mission, we need a Machine Learning Engineer.

Someone who can train LLMs, design Neural Networks, and seamlessly integrate AI with robotics hardware.

Picture R2-D2 not just following instructions, but reasoning through complex scenarios, predicting obstacles, and making independent decisions.

That’s the level of intelligence we’re building.

A team of engineers has already begun the work.

They now need you to build the deep learning models that will drive autonomous systems.

The Mission

To develop machine learning models that will power real-world autonomy.

You’ll train LLMs through their full lifecycle - developing, testing, training, and deploying models that can reason and adapt in dynamic environments.

You’ll build and optimise neural networks that integrate directly with robotics hardware, enabling real-time decision-making.

You’ll develop computer vision and NLP transformer-based systems, applying deep learning for TTS, object recognition, and autonomous navigation.

You’ll optimise ML pipelines for both edge computing and cloud environments (GCP or similar), ensuring efficiency at scale.

What You’ll Bring to the Story

Experience training LLMs and building neural networks for robotics applications.

Hands-on work with deep learning frameworks such as PyTorch and TensorFlow.

A strong background in computer vision, NLP, and edge AI - whether that’s TTS, object detection, or real-time decision-making.

Familiarity with GCP or similar cloud platforms for deploying ML models at scale.

These machines won’t just execute commands.

They’ll think. They’ll learn. They’ll lead.

The galaxy is waiting.

Are you in?

Thaís Amorim – thais@theonset.com.au