Senior Software Engineer, Machine Learning Platform

About Upstart

Upstart is a 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 two-thirds of Upstart loans are approved instantly and are fully automated.

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

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 vision coverage with Health Savings Account contributions from Upstart

401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings

Employee Stock Purchase Plan (ESPP)

Life and disability insurance

Generous holiday, vacation, sick and safety leave

Supportive parental, family care, and military leave programs

Annual wellness, technology & ergonomic reimbursement programs

Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering

Catered lunches + snacks & drinks when working in offices
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At Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location-with our 'digital first' philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).

United States | Remote - Anticipated Base Salary Range

$160,400 - $222,000 USD

Upstart is a proud Equal Opportunity Employer. We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together.

If you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email ***/candidate_privacy_policy
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