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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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Insurance underwriting is the art of pricing risk — and our models do it faster and more accurately than traditional actuarial methods. We serve 6 ins...
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Our models predict game outcomes for 6 professional sports leagues. Not for fun — for regulated sportsbooks that need accurate probability estimates t...
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Our clients deploy ML models in healthcare, lending, and hiring — three domains where biased predictions cause real harm. They hire us to find the bia...
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Traditional AML systems generate 95% false positive alerts. Compliance analysts spend their days reviewing transactions that aren't suspicious, while...
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Our retail clients need to know how much of each product to stock in each warehouse next week. Too much, and they're paying for storage. Too little, a...
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We are a robotics division of a Japanese precision engineering conglomerate. Our robots are deployed in electronics assembly, pharmaceutical packaging...
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Posted 4 months ago
Australia — Sydney (UTC+11)
We build sports analytics products for broadcast and team performance applications in the APAC region. Our primary clients are cricket boards, rugby u...
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Posted 5 months ago
United States — New York (UTC-4)
We are an early-stage genomics company. We are using long-read sequencing and machine learning to identify novel biomarkers for early cancer detection...
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Posted 5 months ago
United Kingdom — London (UTC+1)
We build underwater camera and sensor systems for marine ecology research and offshore infrastructure inspection. Our customers include marine researc...
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We are a Canadian financial technology company regulated by FINTRAC and operating under OSFI supervisory guidelines. We provide lending products to sm...
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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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