Junior AI Engineer — Adaptive Learning

Fatima Al-Rashid

Full-time · Junior · Chicago

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About the role

We are an 18-person EdTech startup. We launched our adaptive learning platform fourteen months ago. We have 26,000 registered learners, a paying school district in Texas, and a pilot underway with two university systems in Australia. Our platform adapts the difficulty and sequencing of learning content based on individual learner performance — the ML piece is the whole point of the product. Right now, that adaptation is powered by a relatively simple model that our CTO built. It works. It is not sophisticated. We know it could be significantly better, and making it better is a material business priority because we are in conversations with three more school districts and the quality of the adaptation is a central part of every evaluation. We are hiring a Junior AI Engineer to work alongside our CTO on improving the adaptation engine. This is not a role for someone who wants to run experiments in a notebook. It is a role for someone who wants to build AI systems in a small company where the work is visible, the feedback is direct, and the learning curve is steep. You will be expected to take genuine ownership faster than a larger company would give you. We think that is a good thing. We want someone who agrees.

Responsibilities

Support the CTO in improving the learner model: feature engineering from assessment response data, model evaluation, and iterative improvement
Build and maintain the data pipeline that feeds the adaptation engine with up-to-date learner performance signals
Write clear documentation for every model change — what was changed, why, and what the evaluation showed
Assist in setting up an experiment framework so that changes to the adaptation model can be A/B tested with real learners
Participate in product discussions with school district partners to understand what adaptation quality means from an educator\'s perspective

Requirements

1–2 years of ML or software engineering experience — a strong final-year project, internship, or bootcamp counts if the work is real
Python at a working level — clean functions, basic testing, and the ability to work in a shared codebase without breaking things
Scikit-learn for classification, regression, and model evaluation under the guidance of a senior engineer
SQL for querying learner performance and assessment response data from our PostgreSQL database
Statistics at a foundational level: train/test splits, evaluation metrics, and the ability to explain what a model output means
Pandas and NumPy for data manipulation and feature engineering
Curiosity about how adaptive learning systems work and willingness to read the relevant literature

Benefits

$72,000 – $88,000 base salary
Full remote — our team spans three time zones and async is how we actually work
0.1% – 0.25% equity on a standard 4-year vest — we are at an early stage and equity is part of the offer
$800 annual learning budget
Direct mentorship from the CTO and a genuine opportunity to grow into a mid-level role within 18 months if you do good work