Manager, Machine Learning

Job not on LinkedIn

🕒 May 5

🇺🇸 United States – Remote

💵 $180k - $210k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Extend

WebsiteLinkedInAll Job Openings

201 - 500 employees

🛍️ eCommerce

🔌 API

🤝 B2B

eCommerce • API • B2B

Extend is a company that helps merchants generate revenue and protect their customers through modern product and shipping protection solutions. They offer protection plans from product failure and accidental damage to shipping issues like porch pirates and damaged deliveries. Extend provides a platform that is easy to integrate with eCommerce platforms like Shopify and BigCommerce. This enables merchants to easily offer protection plans and manage claims, with most being resolved in 90 seconds or less. The company focuses on improving profit margins and enhancing the customer experience by offering easy claim filing and turning customers into long-term advocates.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ Benefits

• 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.