Senior Software Engineer, Machine Learning Platform
UpstartAbout the role
About Upstart
Upstart is the leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload.
Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.
Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!
The Team:
Upstart’s ML Platform team is the engineering team responsible for designing and developing the technology and tools that underpin Upstart’s machine learning capabilities.The team is focused on supporting Upstart’s ML teams in converting research ideas to production models.
As a Senior Software Engineer on the ML Platform team, you’ll be responsible for building an MLOps platform to support machine learning training, process automation, model deployment, and monitoring. Machine Learning is critical to Upstart’s core business, and our greatest competitive advantage lies in the fact that we’re able to innovate on our AI engine quickly.
Position Location - This role is available in the following locations: Remote, San Mateo, Columbus, Austin
Time Zone Requirements - This team operates on the East/West Coast time zones.
Travel Requirements - This team has regular on-site collaboration sessions. These occur 3 days per quarter at an Upstart office. If you need to travel to make these meetups, Upstart will cover all travel related expenses.
How you’ll make an impact:
- Build, maintain, and optimize high-quality software applications that enable machine learning models to be applied to the ever-evolving needs of the business
- Develop the scaffolding, tooling, and infrastructure that allows research scientists to iterate and train large scale machine learning models
- Enable rapid experimentation and iteration in model training code so that we can continuously improve our models
- Build the infrastructure that provides research scientists the ability to access the data and features they need to enhance our models
- Work with Data Engineers, DevOps Engineers, and Research Scientists to ensure that model training and deployment is a repeatable process that relies heavily on automation and workflows (not humans)
What we’re looking for:
- Minimum requirements:
- 5+ years of software engineering experience
- 2+ years of experience building and/or contributing to the advancement of in-house Machine Learning Platforms that enable stakeholders such as modelers or ML-focused Scientists
- Experience as a technical lead of mid-large sized teams working on cross-functional projects
- Experience building and maintaining backend software services and APIs
- Experience with big data, ETL, cloud compute, services, containerization, continuous integration and deployment (CI/CD), and testing frameworks
- Experience with some or many of the following: Python, Typescript, interactive notebooks (Jupyter/Databricks), and AWS
- Good understanding of software development principles and best practices for creating scalable and maintainable systems
- Preferred qualifications:
- Familiarity with cluster compute architectures (i.e.: Kubernetes, serverless architectures such as AWS Lambda, Batch), Databricks, and/or Spark ETL
- 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 dynamics
What you'll love:
- Competitive Compensation (base + bonus & equity)
- Comprehensive medical, dental, and vis
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