Principal Software Engineer, Machine Learning Simulations

Upstart

Remote Actively hiring Posted today Verified listing
Canada Posted today $195,300–$270,400 / year
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Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k
This role $233k
$145k most similar roles pay here $284k

This role pays more than 73% of similar roles. Most pay $174,990–$238,250 — the shaded band above. At the midpoint, this role pays about $233k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Upstart

Upstart is an AI lending platform that partners with banks and credit unions to expand access to affordable credit using non-traditional variables.

Upstart currently has 40 open roles on FindRole.

Listed pay typically runs $177,200–$245,400 across 40 roles with salary data.

Most-posted roles

View all roles at Upstart

At a glance

TL;DR

As a Principal Software Engineer on Upstart's Machine Learning & Simulations Platform (MLSP) team, you will lead the development of an MLOps platform to support model inference, process automation, and observability. Your daily tasks include building high-quality software applications that enable rapid innovation in machine learning models while reducing inference latency. You will also design simulation systems for accurate production environment reflection, collaborating closely with cross-functional teams such as ML, Engineering, Product, and Data Engineering. The role requires proficiency in Python, Kotlin, Databricks, AWS, and experience with model serving technologies like Ray and experimentation frameworks. Ideal candidates exhibit a growth mindset, strong communication skills, and the ability to mentor engineers while contributing to scalable architecture. This position is crucial for Upstart’s mission of reimagining infrastructure to support complex ML models and low-latency inference at scale.

Skills

Python AWS Kubernetes Docker Flask FastAPI MLflow Metaflow gRPC Kafka Spark PySpark Redshift Terraform CI/CD MLOps Ray Prometheus Grafana

What you'll do

  • Build and maintain Upstart's next-generation machine learning platform for increased scale and performance.
  • Develop software applications enabling rapid application of ML models to evolving business needs.
  • Modernize serving infrastructure to reduce inference latency for complex models to just a few seconds.
  • Design simulation systems accurately reflecting production environments, reducing costs and expanding usage across teams.
  • Mentor engineers on distributed systems, MLOps, and scalable architecture to enhance team expertise.

What we're looking for

  • Experience building or contributing to platforms supporting machine learning model simulation.
  • Proficiency with Python, Kotlin, Databricks, and AWS.
  • Track record of mentoring engineers and seeking constructive feedback.
  • Ability to quickly comprehend complex requirements and translate them for stakeholders.
  • Strong background in developing backend software services and APIs.

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