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Tech Stack
Tools & technologiesPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Build and improve data pipelines, dataset tooling, and platform components that support ML training and evaluation
- Partner with ML and applied science teams to translate training/evaluation needs into scalable platform solutions
- Implement quality controls (validation, monitoring, testing) to improve trust in data and pipeline outcomes
- Debug issues across data + ML workflows, driving root-cause fixes and preventing repeat incidents
Requirements
What you’ll need- Solid foundations in ML engineering and data systems
- Experience working with large datasets
- Strong programming skills (e.g., Python)
- Proficient in ML frameworks (e.g., TensorFlow, PyTorch)
- Excited to work in a fast-paced, product-driven environment
Benefits
Comp & perks- Equity packages - we want our success to be yours too
- Inclusive parental leave policy that supports all parents & carers
- An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
- Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ML engineeringdata systemsPythonTensorFlowPyTorchdata pipelinesdataset toolingquality controlsvalidationmonitoring
Soft Skills
problem-solvingcollaborationcommunicationadaptabilityattention to detail