Machine Learning Engineer

1 Days Old

Company We train models that predict how well someone will perform on a job better than a human can. Our platform sources, vets, and onboard expert contractors who help train AI models across a wide range of domains. The technology is used by the top five AI labs. We grew from a $1‑$500M run rate in the last 17 months, averaging 11% week‑over‑week growth in July, 18% in August, and 19% in September, and we maintain profitability while scaling quickly.

Role As a Machine Learning Engineer, you’ll be a key contributor to the backbone of our core product: models and systems that power talent discovery, evaluation, and trust. You’ll blend generalist backend engineering with applied machine learning, designing and deploying models, building scalable infrastructure, and collaborating with product and operations teams to solve real‑world problems.

Responsibilities

Research, train, and deploy production ML models (fraud/cheating detection, candidate engagement and conversion prediction, search/recommendation).

Build backend infrastructure and APIs to serve ML models at scale.

Collaborate with product engineers, sourcing/operations, and other teams to align models with business impact.

Run experiments, analyze results, and iterate quickly to improve model and product performance.

Wear multiple hats—sometimes data scientist, sometimes backend engineer—always a problem solver.

Qualifications

Strong background in backend engineering (Python/Django or similar).

Solid foundation in machine learning and statistics with production experience.

Comfort with ambiguity and a willingness to work across domains.

Familiarity with LLMs, search/recommendation systems, or classification models is a bonus.

Above all: a generalist engineer with curiosity and rigor to tackle diverse problems.

Pay & Benefits Base cash compensation $130‑400k

Generous equity grant

$20K relocation bonus

$10K housing bonus

$1K/month food stipend

Free Equinox membership

Health insurance

Why Join Us

Work on high‑impact problems at the intersection of ML and talent discovery.

Own projects end‑to‑end in a fast‑moving, high‑autonomy environment.

Collaborate with a team of versatile engineers who are comfortable wearing many hats.

Contribute to a mission of empowering a billion people to find their next job.

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Location:
San Francisco
Category:
Engineering

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