Powered by pgvector · cosine kNN
Maincode
About The Role Maincode builds foundation models from first principles on Australian infrastructure. We design architectures, run our own compute, shape the training process, and operate the systems that serve our mod…
Your match
See how you fit
Scored against this job in seconds
Your account
Sign in to apply
Your profile and your match for this job appear right here.
sign in above to apply · via jobs.ashbyhq.com
About the role
About The Role
Maincode builds foundation models from first principles on Australian infrastructure. We design architectures, run our own compute, shape the training process, and operate the systems that serve our models.
We have built Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live; we are scaling the next version of Matilda and deploying and serving it live for public access.
We are looking for AI researchers who want to work on the core architecture, training, and evaluation of large-scale language models that power Matilda.
This role is not focused on incremental benchmarking or paper output. You will work directly with the engineers running large-scale training systems and help design models that learn efficiently and behave reliably in production.
What You Would Actually Do
You will work across the model development loop, from research questions to training runs to evaluation.
This Includes
Designing and testing architecture changes and training regimes for large language modelsRunning controlled experiments at scale and isolating causal effectsStudying failure modes in reasoning, generalisation, robustness, and representationShaping objectives, data mixtures, and optimisation choices that influence model behaviourBuilding and refining evaluations that measure capability and reliability, not just scoresAnalysing training dynamics using logs, metrics, and model outputsCollaborating with ML systems engineers on distributed training and training operationsWriting clear internal notes that turn experimental results into design decisions
You will spend substantial time in code, training runs, logs, and evaluation outputs. The goal is clarity about what improves the model and why.
What We Are Looking For
We care about depth of reasoning, experimental discipline, and the ability to make progress under ambiguity.
We Expect
Hands-on experience writing and running production-grade ML or research codeStrong Python and experience with PyTorch or JAXSolid understanding of transformer-based language models and the basics of pre-training and evaluationAbility to design experiments, interpret results, and communicate tradeoffs clearlyComfort working close to infrastructure, performance constraints, and operational realityInterest and exposure to reasoning-oriented architectures and training methods beyond standard approaches, and beyond standard LLMs
Nice to have
Experience with distributed training concepts and tooling (data parallel, tensor parallel, sharding, checkpointing)Experience running training across multiple nodes and managing long training cyclesFamiliarity with large-model training stacks and frameworks (for example Megatron-style systems, DeepSpeed-like tooling, FDSP or similar)Comfort across the full workflow: training, evaluation, and deployment constraintsExperience working in ROCm-based environments
How You Would Work
This is hands-on research. You will use code as a primary tool for thinking.
You Will Be Expected To
Move between theory and implementation quickly and preciselyPrefer controlled experiments over broad sweepsUse logs, metrics, and model behaviour to guide decisionsWork closely with engineering counterparts to scale and validate ideas
What This Role Is Not
It is not a product research roleIt is not prompt engineeringIt is not fine-tuning someone else’s model and shipping wrappers around external APIs
You will work on Matilda, trained from scratch on our infrastructure, and pushed until its behaviour is understood and improved.
Why Maincode
Maincode builds and operates the full stack: training infrastructure, model code, evaluation systems, and deployment. We run one of the largest private AI compute environments in Australia, built for the sole purpose of training and deploying large scale models.
If you want to work directly on training and evaluating a large language model built from scratch, this is the only role in Australia that will put you inside that work.
Note
This is a full time role based in Melbourne, working closely with our in person team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.
sign in above to apply · via jobs.ashbyhq.com
Your job hunt, handled
Ask about any role and get a straight answer on your fit. Then stop searching: new matches land in your WhatsApp the moment they’re listed.
Free for jobseekers
Maincode
About the role Maincode builds foundation models from first principles on Australian infrastructure. We design architectures, run our own compute, shape the training process, and operate the systems that serve our mod…
Maincode
About the role Maincode is training Matilda, the first large language model built and trained from scratch in Australia. Our new compute cluster is live, and we are now scaling the next version. This role sits directl…
Maincode
Maincode is mission-focused. That means we care about shipping Matilda, and we care about the people we do it with. Everything else is secondary. Matilda is Australia's first publicly available conversational AI platf…
Maincode
Maincode is mission-focused. That means we care about shipping Matilda, and we care about the people we do it with. Everything else is secondary. Matilda is Australia's first publicly available conversational AI platf…
Maincode
About Maincode Maincode is an AI research and engineering company and home to Matilda, Australia’s first and only large language model trained from scratch. We operate our own advanced AI infrastructure in local data-…
NinjaTech AI
Come build the intelligence behind autonomous AI employees. At NinjaTech AI, we’re building AI systems that do more than answer questions. Our agents plan, reason, use tools, operate computers, collaborate with humans…