Software Engineer, Machine Learning

Ema, Vancouver, BC

Ema has this job in 1 other place

What you need

Depth you can defend. Substantial work in at least one of agent/tool-use systems, post-training, reward modeling or RL environments, retrieval and memory, or evaluation design. Be ready to explain the mechanism, the alternatives you rejected and the failure modes you found. One area you can teach us beats five you’ve touched.
Evidence of zero-to-one ownership. A system, model or research project you took from an ambiguous problem to a working result. We want to understand your contribution, the tradeoffs you made, and what changed when the work met real users or realistic tasks.
Statistical judgment. You can size an experiment, choose meaningful baselines and held-out tests, and account for variation across tasks, seeds and repeated runs. You can distinguish a real improvement from judge bias, data leakage or a benchmark shortcut.
Production engineering judgment. You can debug across the model and system boundary, isolate a failure, and turn the result into maintainable production code.

Ema, Vancouver, BC

Ema has this job in 1 other place

Depth you can defend. Substantial work in at least one of agent/tool-use systems, post-training, reward modeling or RL environments, retrieval and memory, or evaluation design. Be ready to explain the mechanism, the alternatives you rejected and the failure modes you found. One area you can teach us beats five you’ve touched.
Evidence of zero-to-one ownership. A system, model or research project you took from an ambiguous problem to a working result. We want to understand your contribution, the tradeoffs you made, and what changed when the work met real users or realistic tasks.
Statistical judgment. You can size an experiment, choose meaningful baselines and held-out tests, and account for variation across tasks, seeds and repeated runs. You can distinguish a real improvement from judge bias, data leakage or a benchmark shortcut.
Production engineering judgment. You can debug across the model and system boundary, isolate a failure, and turn the result into maintainable production code.