Upstart is looking to reimagine its Machine Learning & Simulations Platform (MLSP) infrastructure to support the growing complexity of ML models, the demand for low-latency inference, and the accuracy needed to simulate the dynamics of its borrower-lender marketplace at scale. This role will help build an MLOps platform to support machine learning model inference, process automation, model deployment, and observability, and a marketplace simulation platform to support rapid innovation.
Requirements
- 6+ years of software engineering experience including several building and contributing to in-house Machine Learning Platforms
- Experience building and maintaining backend software services and APIs
- Proficiency with some or many of the following: Python, Kotlin, Databricks, and AWS
- Familiarity with model serving technologies like Ray, simulation platforms, experimentation frameworks
- Proficiency with Flask, FastAPI, Metaflow, MLflow, gRPC, Kafka, Spark/PySpark, ETL/ELT, Redshift (or similar)
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
Other
- 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
- 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
- The team operates on the East/West coast time zones.
- As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.
