Data Scientist – Machine Learning

The Role
As a Data Scientist (Machine Learning), you will be responsible for researching, building and training deep learning models. You will also need to work with the data team to collect and process structured and unstructured datasets to build deep learning models. The models will vary from simple random foreset algorithm to complex multi-modal autoregressive transformer models.
With the data team, you will ensure that the model remains relevant and build pipelines to retrain the model if the data changes, or as we enter new markets with different but similar datasets.
You will be working with data engineers, machine learning engineers and backend software engineers to ensure that the deployed models are scalable and performant.
Reporting to: The Head of Engineering.
Required Skills
  • Knowledge of PyTorch and common libraries (e.g. Huggingface transformers, PyTorch lightning, Scikit-learn).
  • Strong knowledge of recent deep learning advancements, primarily transformers. (e.g. ViT, BeiT, GPT & LLM models)
  • The use of automated ML solutions (e.g. GCP AutoML / Azure AutoML) DOES NOT constitute as experience.
  • Strong Python & SQL skills.
Preferred Skills
  • Experience with cloud computing is strongly preferred. (AWS, GCP or Azure).
  • Experience with distributed LLM training optimization (e.g. DeepSpeed, QAT, model parallelization).
  • Experience with cloud-based training is a plus (e.g. Vertex AI, Sagemaker Training).
What you will be doing
  • Work with the engineering team to develop and tune deep learning models.
  • Design data collection / cleaning processes to collect relevant datasets to train deep learning models.
  • Problem-solving and project managing.
  • Undertake any other duties relevant to the position as instructed by your immediate supervisor.

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Acknowledgement of Country

U Group acknowledges the deep connections of Aboriginal and Torres Strait Islander communities to Country. We pay our respects to the Whadjuk Nyoongar people, who are the Traditional Owners of the land our offices are on in Perth, Western Australia