Sr. Manager, Software Engineering - Machine Learning Simulations

About Upstart

At Upstart, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence.

As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 3,000 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress.

We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City, you’ll have the support to work in the way that works best for you.

If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you.

The Team:

Upstart's Machine Learning and Simulations Platform team builds and operates the infrastructure behind ML model training, features engineering, inference, and marketplace simulation. Our simulation platform answers one question before any change reaches a borrower: what would this new ML model, price, or fee have produced for real applicants? It replays historical data through production pricing logic in isolated environments, and it is now the shared tool every machine learning team at Upstart uses to size the impact of a launch. Our priorities are reliability teams can bet a launch on, fidelity to production we can prove, cost per simulation stays in check as usage grows, and coverage that extends across the lending funnel and into new loan products.

As the Senior Engineering Manager, Machine Learning Simulations at Upstart, you will lead the team that owns this platform. Today machine learning teams run roughly a thousand simulations a month on it. Your job is to make it production-grade, cut its cost while usage doubles, and open it to Analytics and Finance teams who need the same answers about pricing and portfolio strategy. You will work across machine learning, pricing, product, analytics, and infrastructure teams, many of whom own the logic your platform has to reproduce faithfully.

How you’ll make an impact

Own the engineering roadmap for Upstart's marketplace simulation platform, and decide which teams and use cases it serves next

Lead, coach, and grow a team of engineers working across distributed services, offline data pipelines, and large-scale compute

Raise simulation reliability and accuracy to a level teams trust for launch decisions, including automated checks that detect drift between simulated and production results

Reduce the cost of each simulation as usage grows, through smart architecture and compute choices

Extend simulation coverage across the lending funnel and into new loan products, partnering with the teams who own each stage of pricing and decisioning logic

Turn recurring questions from machine learning, analytics, and capital markets partners into self-serve simulation workflows

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience

8+ years of software engineering experience, including 3+ years of engineering management experience

Experience leading engineering teams that build and operate backend platforms or distributed systems in production

Experience delivering platform or infrastructure programs that span multiple teams

Proficiency with some or many of the following: Python, Kotlin, AWS, Kubernetes, Databricks, Spark

Preferred Qualifications

Knowledge of simulation, backtesting, experimentation, or offline model evaluation systems

Experience supporting machine learning teams or operating MLOps infrastructure, including model inference, workflow orchestration, and offline feature pipelines