Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructure
Translate business problems into well-framed ML solutions: defining what to model, what success looks like, and where ML adds value vs. simpler approaches
Design and maintain feature engineering pipelines for model development
Drive experiment design and statistical rigor: ensuring models are evaluated with sound methodology before and after launch
Monitor model quality in production, tracking performance over time, detecting data drift, and determining when to retrain
Cultivate a culture of learning and collaboration within and across partner teams
Perform design and code reviews to raise the technical excellence bar
Hire, mentor, and coach data scientists

6+ years of work experience building and deploying machine learning systems into production
2+ years experience mentoring and managing ML teams
Strong proficiency in Python and SQL
Strong understanding of ML fundamentals: model selection, evaluation methodology, feature engineering, and common failure modes
Hands-on experience with PyTorch, scikit-learn, and XGBoost (or similar gradient boosting frameworks)
Strong people leadership skills with the ability to develop ML talent
Excellent stakeholder management, with a track record of working cross-functionally to deliver results
Empathy and humility

Remote (City/Region) — San Francisco

Estimated Pay Range: $180,000-$210,000 per year salaried
Working with a great team from diverse backgrounds in a collaborative and supportive environment
Competitive salary based on experience, with full medical and dental & vision benefits
Stock in an early-stage startup growing quickly
Generous, flexible paid time off policy
401(k) with Financial Guidance from Morgan Stanley

Extend is hiring a Manager, Machine Learning