12 days ago
Sydney, AustraliaMid Level
Responsibilities
- Design, code, test, and deploy machine learning pipelines using Python, SQL, AWS, and GCP.
- Build AI products using generative AI, LLMs, and traditional machine learning techniques.
- Prototype proofs of concept and evaluate new ideas with senior engineers.
- Support data processes through ad-hoc analysis, automated dashboards, and self-service reporting tools.
- Analyze data coverage and quality across internal and external datasets.
- Follow software development practices including test-driven development, continuous delivery, and pair programming.
- Share operational responsibility for software using the organization’s “you build it; you run it” philosophy.
- Collaborate with business stakeholders and contribute to team learning and mentoring.
Requirements
- Programming ability in SQL, Python, R, C#, or similar languages.
- Passion for machine learning, deep learning, generative AI, time-series analysis and forecasting, and software development.
- In-depth knowledge of the machine learning model lifecycle.
- Experience with ML and hosting libraries such as XGBoost, LightGBM, Scikit-learn, PyTorch, Keras, HF models, Transformers, FastAPI, or Flask.
- Ability to clean, analyze, and interpret large datasets and identify incorrect or inconsistent data.
- Basic understanding of cloud service providers including AWS, Azure, and Google Cloud Platform and their core services and applications.
- Ability to communicate and collaborate effectively with business stakeholders.
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or a similar discipline.
Benefits
- Permanent role based in Sydney with a hybrid and flexible working approach.
- Flexible leave options including birthday leave and the ability to purchase additional leave.
- Flexible parental leave for primary and secondary carers.
- Volunteering leave, community grants, matched payroll giving, and a community café supporting charity through the Because We Care program.
- Hackdays and opportunities for learning, mentoring, and professional growth.
- Commitment to diversity, equity, and inclusion.
Tech Stack
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