Senior Software Engineer, Upstart

• Bachelor’s degree in Computer Science, Engineering, or Mathematics, or a related field (or its equivalent) + 4 years of experience
• Experience owning delivery of ML-powered features from design through production deployment and measurement
• Hands on experience designing or contributing to experimentation systems, including running controlled experiments in live environments
• Experience building and maintaining data processing systems or pipelines that support model-driven decisioning

Desirable

• Our Servicing Engineering teams are building intelligent systems that personalize borrower experiences using machine learning. Today, most borrowers are treated the same, regardless of their financial situation. We’re changing that
• As a Senior Software Engineer in this role, you’ll redefine how servicing decisions are made. You’ll turn machine learning models and signals into systems that shape real borrower interactions, including who we reach, how we engage, and which strategies we apply
• You’ll evolve and scale our decisioning and experimentation systems to support faster iteration and more reliable measurement of strategy performance against borrower and business outcomes
• Reporting to a Senior Engineering Manager, you’ll partner closely with Product and Machine Learning teams to run experiments, productionize model outputs, and build feedback loops that connect real-world outcomes back to model and strategy improvements
• Improve how Servicing decisions are made by embedding machine learning models into product and operational workflows
• Enable faster learning and safer iteration by advancing our experimentation platform and improving how we evaluate strategy performance
• Increase the effectiveness of personalization strategies by designing and running controlled experiments that translate into measurable improvements
• Scale model-driven decisioning through resilient feature pipelines and real-time data integrations
• Define clear metrics and guardrails to ensure ML-powered systems remain measurable, explainable, and compliant as they shape more Servicing decisions