Sr. Manager, Software Engineering - Machine Learning Simulations

Upstart is an AI lending marketplace that uses advanced technology to expand access to affordable credit. The Senior Engineering Manager will lead the Machine Learning Simulations Platform team, owning its roadmap, reliability, accuracy, cost efficiency, and expansion across lending products while partnering with machine learning, pricing, analytics, finance, and infrastructure teams.

Responsibilities:

• 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

Requirements:

• 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
• The team operates on the East/West coast time zones
• 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
• Knowledge of lending, pricing, credit risk, or marketplace economics
• Ability to treat compute cost and efficiency as an engineering goal alongside reliability
• Ability to build shared platforms where partner teams own part of the logic, and to keep those interfaces steady as systems evolve
• Experience developing senior engineers and emerging engineering leaders