Principal Software Engineer, Machine Learning Simulations

Upstart is an AI lending marketplace focused on reducing the cost and complexity of borrowing for Americans. They are seeking a Principal Software Engineer specializing in Machine Learning Simulations to build an MLOps platform and a simulation platform that supports rapid innovation and enhances machine learning model inference.

Responsibilities:

• Build, maintain, and optimize Upstart’s next-generation machine learning and simulation platform, enabling increased scale, performance, and confidence in decisioning
• Develop high-quality software applications that enable machine learning models to be applied to the ever-evolving needs of the business
• Enable the modernization of our serving infrastructure, reducing inference latency to just a few seconds for our most complex models
• Design and contribute to our simulation systems to more accurately reflect production environments, reducing simulation cost and enabling broader usage across teams
• Communicate closely with cross-functional partners from ML, Engineering, Product, and Data Engineering teams, keeping all stakeholders informed
• Mentor engineers across the team, sharing expertise on distributed systems, MLOps, and scalable architecture

Requirements:

• Bachelor's degree in Computer Science, Engineering, or Mathematics, or a related field (or its equivalent) + 8 years of experience
• Experience building or contributing to platforms or systems that support machine learning model simulation
• Experience building self-serve or configuration-driven tooling for internal stakeholders
• Experience building and maintaining backend software services and APIs
• Proficiency with some or more of the following: Python, Kotlin, Databricks, and AWS
• Exhibits a growth mindset - you're not afraid to pick up new technologies that are best for the task, and learn from others
• Ability to quickly comprehend and reiterate complex requirements from product or engineering leadership and translate those to both technical and non-technical stakeholders
• Track record of successfully mentoring and developing other engineers around you while seeking out and appreciating constructive feedback
• Familiarity with model serving technologies like Ray, and experimentation frameworks
• Proficiency with Flask, FastAPI, Metaflow, MLflow, gRPC, Kafka, Spark/PySpark, ETL/ELT, Redshift (or similar)
• Excellent quantitative reasoning skills with interest in working at the intersection of engineering and machine learning
• Strong sense of ownership and accountability for the quality and timely delivery of work
• Proven ability to effectively analyze and solve complex problems
• Excellent written and verbal communication skills with stakeholders, peers and product owners
• Ability to thrive both in self-directed work environments and in collaborative settings, contributing positively to team dynamic