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Remote Scikit-learn Jobs
Browse vetted remote Scikit-learn positions at AI companies — ML engineering, classical model development, and feature engineering roles.
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Posted 2 months ago
Sr. Solutions Architect - Digital Native Business, Strategics
As a Sr. Solutions Architect on the team supporting the strategic Digital Natives Business (DNB) customers, you will shape the future of the Data &...
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Posted 2 months ago
Solutions Architect - Digital Native Business, Named Accounts
FEQ327R210While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE As a...
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Posted 5 months ago
AI Data Analyst
Data Analyst – Prolific Works (Remote) Role Overview The Data Analyst at Prolific Works plays a key role in transforming platform data into insights...
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Our merchants process a little over $14B a year through Ilvix Works, and for most of them a single percentage point of authorization rate is worth mor...
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Our explainability team has five people: two data scientists, a compliance specialist, a designer and a product lead. We build tools lenders use to ex...
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Our clients are consumer brands spending heavily on retail media networks like Amazon Ads, Walmart Connect and Tesco's in-store screens. The person in...
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Spark for offline features, Kafka for real-time signals, and a gradient-boosted ranker that serves around 30 million queries a day. That is the core o...
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We just signed two new enterprise retail clients who are losing revenue to coordinated fake review networks, and they need detection running before th...
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We just closed a partnership with three mid-market private equity funds who need a faster way to screen inbound deal flow before it reaches a partner'...
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Bad actors sometimes inject deliberately wrong labels into crowdsourced annotation batches to sabotage training data, and our current quality checks c...
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Role guide
What to expect in remote Scikit-learn jobs
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.
What you'll work on
- Build and deploy classification or regression models for business predictions
- Design feature engineering pipelines that process raw data for ML models
- Benchmark classical ML approaches against deep learning alternatives
- Maintain and retrain production models as data distributions shift
What companies look for
- Strong understanding of model evaluation — cross-validation, bias-variance, metrics
- Feature engineering experience — encoding, imputation, scaling, selection
- MLflow or similar experiment tracking integration
Frequently asked questions
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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