Head of Data

Maincode makes Matilda, an Australian-made AI stack we own end to end, from tin to token. We own and operate our own infrastructure here in Australia, we train and maintain our own frontier models, and we run multiple surfaces on top of them, including chat, coding and API. Everything we ship is built on capability we control ourselves. We are hiring someone who cares about that. You should be passionate about Australian-made technology, a builder first, and keen to execute at the frontier of data engineering and model training.

A frontier model is only as capable as the data it learns from. We are building a dedicated data organization to source, process, and refine the high value training data that powers Matilda. Our goal is to build the most comprehensive, high quality, and contextually accurate Australian training data catalog in the world.

You will be the foundational leader of this team. You will own the entire lifecycle of our training data catalog. This includes web scale crawling, data licensing, filtering, deduplication, and quality control. We need a technical leader who knows how to recruit top tier data engineers and build a machine capable of turning petabytes of raw information into clean, proprietary training sets.

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  Build and lead a high performing team of data engineers, ML engineers, and data operations specialists.

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  Design and manage the architecture for web scale data crawling, ingestion, and storage.

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  Develop robust pipelines for data filtering, cleaning, deduplication, and formatting to ensure the highest quality inputs for model training.

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  Source and secure proprietary, high value datasets specifically tailored to the Australian context, including navigating licensing and private partnerships.

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  Work directly with our core training team to iterate on data mixtures, evaluate data quality, and respond to model performance feedback.

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  Establish the operational standards for data governance, privacy, and security across all our datasets.

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  Extensive experience leading data engineering or machine learning data teams at scale.

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  Deep technical knowledge of distributed data processing frameworks and petabyte scale storage systems.

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  Hands on experience building pipelines for web scraping, data extraction, text processing, and quality filtering.

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  A proven track record of recruiting, mentoring, and managing elite technical talent.

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  A strategic understanding of the data landscape, especially regarding sourcing proprietary information and handling complex unstructured data.

• Direct experience building pre-training or post-training datasets for large language models.

• A strong network within the Australian technology, academic, or media ecosystem to facilitate unique data partnerships.

• Must have the right to work in Australia.

• Willingness to undergo background checks as required.

Leaders who understand that high quality data is the true moat of any frontier model. If you care about Australian-made technology and you would rather spend your week optimizing data mixtures, unblocking your engineering team, and securing high value data sources than sitting in steering committee meetings, you will do well here.