Machine Learning Engineer (LLM)
The Onset
Date: 1 day ago
City: Sydney, New South Wales
Contract type: Full time
Job Description
“I trained the model... but I’ve never seen it fly.”
If that’s ever crossed your mind, this might be the role that changes that.
We’re building AI systems that actually control autonomous machines in the real world - not just simulations, not just benchmarks. We’re working on drones that interpret spoken commands, break them into steps, reason through next actions, and deploy tools - all powered by models you’ve helped train.
We’ve got the prototype working. Now we’re scaling. That’s where you come in.
The Role
We’re looking for a Machine Learning Engineer who knows how to train Large Language Models from scratch - someone who’s worked with real datasets, not just wrappers around APIs. You’ll be designing the systems that sit between a human voice and an autonomous drone’s behaviour, helping us build recursive agentic frameworks that actually think before they act.
And yes - if you've spent the last few years doing deep research in LLMs, and you're ready to take that work out of the lab and into the field, we want to hear from you.
What You’ll Be Doing
We’re open to junior candidates (2–3 years’ experience) if you’ve gone deep into LLMs and are ready to move fast. What matters most to us: hunger, curiosity, and deep technical understanding.
We're also open to junior candidates, as well as PhD graduates or anyone with a research background in LLMs/NLP/ML - especially if you're ready to leave academia behind and make a tangible impact.
We’re also open to relocation support, and yes - we’ll sponsor the right person if they’re not based in Australia yet.
You won’t just be building another chatbot. You’ll be designing the brain of a robot that reasons, decides, and acts - in the wild.
If that sounds like something worth doing, let’s talk.
Thaís Amorim - [email protected]
https://www.linkedin.com/in/thaispamorim/
“I trained the model... but I’ve never seen it fly.”
If that’s ever crossed your mind, this might be the role that changes that.
We’re building AI systems that actually control autonomous machines in the real world - not just simulations, not just benchmarks. We’re working on drones that interpret spoken commands, break them into steps, reason through next actions, and deploy tools - all powered by models you’ve helped train.
We’ve got the prototype working. Now we’re scaling. That’s where you come in.
The Role
We’re looking for a Machine Learning Engineer who knows how to train Large Language Models from scratch - someone who’s worked with real datasets, not just wrappers around APIs. You’ll be designing the systems that sit between a human voice and an autonomous drone’s behaviour, helping us build recursive agentic frameworks that actually think before they act.
And yes - if you've spent the last few years doing deep research in LLMs, and you're ready to take that work out of the lab and into the field, we want to hear from you.
What You’ll Be Doing
- Designing, training, and fine-tuning LLMs from scratch (no shortcuts)
- Building out chain-of-thought frameworks and multi-step reasoning agents
- Working closely with robotics and speech teams to bring your models to life
- Contributing to an evolving agent architecture with plans for vision-language integration
- Helping us make the leap from early success to scalable, field-tested autonomy
- Real experience training transformer-based LLMs (e.g. GPT, LLaMA, custom)
- Comfort building and managing your own datasets
- Familiarity with agentic AI, tool-calling, or recursive planning
- Exposure to speech-to-text pipelines or model context protocols (MCP)
- Passion for deploying ML models in the real world - not just reading papers about it
- The drive to build something no one else in Australia is doing right now
- A genuine hunger to learn, build, ship, and improve
We’re open to junior candidates (2–3 years’ experience) if you’ve gone deep into LLMs and are ready to move fast. What matters most to us: hunger, curiosity, and deep technical understanding.
We're also open to junior candidates, as well as PhD graduates or anyone with a research background in LLMs/NLP/ML - especially if you're ready to leave academia behind and make a tangible impact.
We’re also open to relocation support, and yes - we’ll sponsor the right person if they’re not based in Australia yet.
You won’t just be building another chatbot. You’ll be designing the brain of a robot that reasons, decides, and acts - in the wild.
If that sounds like something worth doing, let’s talk.
Thaís Amorim - [email protected]
https://www.linkedin.com/in/thaispamorim/
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