Machine Learning Engineer

Own the models the whole company is named after: the Franchise Readiness Score, the Compatibility Index, and the calibration that keeps both honest.

Team Intelligence Type Full-time Location Remote — anywhere with 4 hours overlap with Eastern Time

The FRS is a number people make life-changing decisions on. That makes calibration a product requirement rather than a metric: a 78 has to mean the same thing this quarter as it did last, and has to mean the same thing for two franchisees who are not alike.

The interesting problem is not accuracy, it is fairness and drift. The score must not learn proxies for things it has no business scoring, and it must stay stable as the population it sees changes. You will spend as much time on evaluation and explanation as on modelling.

What you will do

• Own the FRS and FCI models end to end — features, training, evaluation, deployment
• Build the calibration and drift monitoring that proves a score still means what it meant
• Make every dimension explainable: a franchisee is owed the reason, not just the number
• Audit for proxy bias, and design the evaluation that would catch it
• Work with the domain rules rather than around them — the score lives inside consent

What we are looking for

• Solid applied ML, and judgement about when a model is the wrong answer
• You have shipped a model into production and lived with its failures
• You can explain a prediction to someone it affects, in their language
• Rigorous about evaluation — you design the test before you like the result
• Comfortable that the honest answer is sometimes 'we cannot score that'

Nice to have

• Credit scoring, underwriting, admissions, or another consequential-decision domain
• Fairness and explainability work you can point at
• Experience calibrating a score that non-technical people act on

The stack

• Python
• PyTorch
• FastAPI

Remote

This role is fully remote. We care about overlap, not postcode — four hours with Eastern Time is enough.

How we hire

A conversation, a piece of real work paid at our rate, and a call with the team you would join. No whiteboard puzzles, no unpaid take-homes.

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