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Browse vetted remote Scikit-learn positions at AI companies — ML engineering, classical model development, and feature engineering roles.
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You'll be the third fraud analyst on a team of nine, working directly with the returns operations group. We already have a solid transaction dataset a...
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Every day, alerts from this system protect more than 400 brands from fake social accounts and phishing domains before customers ever see them. Built o...
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Our fraud team is drowning in loan applications that need manual triage before underwriting even starts, and legitimate applicants are waiting days be...
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Small creators who rely on affiliate income deserve a fair system, not one bad actors can game with cookie-stuffing and fake conversions. Built on our...
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As a fully async team spread across 7 time zones, we believe great engineers don't need to be in the same room to do their best work. We already have...
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We're building the tool that tells ops teams which planned maintenance windows are actually risky before they happen. Our problem is that half of our...
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We already have a solid valuation engine covering long-term rental and resale pricing across our markets. What's missing is a model tuned specifically...
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Our mission is to make personalization feel helpful instead of exhausting, and this role sits right at the center of that. The team combines data scie...
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We serve independent artists and small labels who lose real money every time a royalty split gets calculated wrong on a collaborative track. Fast-movi...
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We just won a mandate to build default risk coverage for municipal bonds after our existing corporate credit models proved the concept, and we're scal...
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Role guide
Scikit-learn is the workhorse of applied machine learning. Remote Scikit-learn jobs involve building production ML models for classification, regression, and clustering tasks — often as part of a larger data platform or AI feature pipeline. Many AI companies use Scikit-learn alongside PyTorch or XGBoost in production systems.
Are there remote jobs specifically for Scikit-learn engineers?
Scikit-learn is rarely the only requirement — it typically appears alongside Python, Pandas, and sometimes PyTorch. Roles involving applied ML, prediction systems, or feature engineering are the best fit.
Is Scikit-learn relevant if a company uses PyTorch or TensorFlow?
Yes. Scikit-learn handles preprocessing, classical baselines, and evaluation utilities that complement deep learning frameworks. Most ML engineers use Scikit-learn daily regardless of their primary modelling framework.
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