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Machine Learning Engineer
Own evaluation, retrieval quality, and the line between a demo and a production system.
You will decide what is actually production-ready. That means building the eval harness before the feature, and being the person who blocks a launch when the numbers do not hold.
What you will do
- Build evaluation suites for model behaviour and keep them running in CI
- Own retrieval quality: chunking, embeddings, reranking, and the measurement of all three
- Work in multilingual settings: Bahasa Malaysia, English, and Mandarin in the same pipeline
- Publish what you learn, internally and sometimes externally
What we look for
- Hands-on applied ML experience in production, not only research
- Strong software engineering fundamentals
- Scepticism toward benchmark numbers, including your own
How hiring works here
One conversation about your work, one working session on a real problem (paid, and scoped to a few hours), and a conversation with the team you would join. We give a decision within five working days of the last step, either way.
Think you would be good here?
The fastest route in is to show us something you built.