Senior Manager, Software Engineering – Personalization, ML Enablement

November 19

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

🏈 Ohio – Remote

Although this job is listed in Ohio, this company may be open to hiring remote in other states.

+1 more states

🏄 California – Remote 🏈 Ohio – Remote 🤠 Texas – Remote

💵 $180.6k - $250k / year

⏰ Full Time

🟠 Senior

👮‍♀️ Software Engineering Manager

🦅 H1B Visa Sponsor

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Upstart

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Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. As we transitioned to being a public company, we’re now poised to leverage our domain expertise and revolutionize every aspect of lending and credit risk evaluation. We’ve recently expanded our offerings to include automobile refinancing and we plan to take on more verticals as the business grows.

1001 - 5000 employees

📋 Description

• Define and drive the multi-year technical roadmap for personalization and selection systems across Upstart’s servicing domain. • Build and scale a high-caliber team of engineers and ML practitioners that can deliver both infrastructure and ML models in production. • Launch ML-powered personalization models that adapt borrower experiences in real time, reducing delinquencies and increasing satisfaction. • Lead the development of experimentation platforms (e.g., A/B testing, bandits) that accelerate model iteration and feature evaluation. • Collaborate cross-functionally with Product, Data Science, and ML leadership to ensure alignment with borrower and business outcomes. • Embed fairness, explainability, and governance into all personalization efforts to ensure responsible AI practices at scale. • Establish clear metrics for model impact (e.g., lift, latency, precision/recall) and build observability practices for robust operations.

🎯 Requirements

• 10+ years of software engineering experience, including 4+ years in people management roles. • Hands-on experience with ML systems, personalization engines, recommendation platforms, or experimentation infrastructure. • Deep technical understanding of machine learning fundamentals, data pipelines, and deploying models at scale. • Proven ability to hire and grow high-performing ML and engineering talent in fast-paced, ambiguous environments. • Strong strategic thinking with the ability to connect engineering efforts to business and borrower outcomes. • Effective communication skills and a track record of cross-functional leadership.

🏖️ Benefits

• target bonuses • equity compensation • generous benefits packages (including medical, dental, vision, and 401k)