Job from partner
Send messageDescription of the job
Maincode is building sovereign AI models in Australia. We are training foundation models from scratch, designing new reasoning architectures, and deploying them on state-of-the-art GPU clusters. This is not fine-tuning someone else’s work. This is building from first principles.
As an AI/ML Engineer, you’ll be part of the team that makes this real. You’ll work on both sides of the problem: how models are trained and how they run in the world. You’ll design and build the systems that power large-scale training runs and efficient inference. You’ll work closely with our AI Researchers to implement the latest algorithms and ideas.
This is a deep engineering role. You’ll be writing a lot of code, instrumenting systems, optimizing performance, and debugging weird, messy edge cases in distributed training and model serving. If you love figuring out how foundation models really work under the hood, this is your team.
What you’ll doBuild and scale training pipelines for sovereign foundation models like large language models and other architectures
Design efficient inference systems that run these models in real-world environments
Optimize data pipelines, tokenization, batch prep, and distributed training at multi-node scale
Build deep observability into training and inference, improving performance, correctness, and efficiency
Debug and troubleshoot the hardest parts of model training and deployment, including distributed failures, GPU bugs, data inconsistencies, and scaling limits
Work closely with AI Researchers to translate cutting-edge algorithms into working systems
Establish strong ModelOps practices to ensure reproducibility, reliability, and continuous improvement across the full lifecycle of foundation models, from initial experiments to production deployment
Passionate about how models are built, trained, and run, especially large-scale foundation models
Driven by curiosity about model internals, training dynamics, and system-level performance
Excited to work across both training and inference, not just one side of the ML stack
Skilled in Python and ML frameworks like PyTorch or JAX. Familiarity with distributed compute (CUDA, Triton, NCCL, etc.) is a bonus but not required
Constantly learning, whether it’s reading open-source repos, replicating research ideas, or designing your own tools to explore a problem
Hands-on and determined. You like writing code, running experiments, and figuring things out
Motivated to help build sovereign AI capability here in Australia
We are a small team building some of the most advanced AI systems in Australia. We are creating new foundation models from scratch, not just using what’s already out there.
We operate our own GPU clusters, run large-scale training, and work closely across research and engineering to push the frontier of what’s possible.
You'll be surrounded by people who:
Care about model internals, not just outputs
Build things that work, at scale
Take pride in learning, experimenting, and shipping
Want to help Australia build independent, world-class AI systems
