Machine Learning Engineer

About the role

We apply machine learning where it changes an outcome — forecasting demand, classifying inbound work, extracting structure from documents that were never designed to be machine-readable. Your job is to make that work reliably, not just in evaluation.

What you will do

• Frame problems with the people who own the outcome, and say no when a model is the wrong tool.
• Build data pipelines, training and evaluation you can rerun without ceremony.
• Ship models into products and keep them honest once real inputs arrive.
• Instrument what you deploy: drift, cost and quality, visible to the whole team.

What we are looking for

• Strong Python, and experience taking a model all the way into production.
• Solid grounding in evaluation — you know how a good offline number becomes a bad live one.
• Comfortable with the engineering side: containers, CI, queues, storage.

Nice to have

• Applied experience with language models beyond prompting: retrieval, evaluation harnesses, cost control.
• Time-series or forecasting work in an operational setting.

How to apply

Apply through the form on our contact page, with a short note about a model you put into production and what it taught you.