Senior ML Platform Engineer (Remote)

Upstart; Northern (KY); Hybrid; USD 167,000 - 230,000; Full time

Benefits offered by this job

Competitive pay

Annual equity grants

401k with company match

ESPP

Health coverage

Job summary

Upstart is seeking a Senior Software Engineer for the ML and Simulations Platform to build an MLOps stack and a marketplace simulation layer. You will own backend services, feature pipelines, and model deployment, partnering with ML, Data, and Product teams to accelerate AI-driven decisions.

The role emphasizes scalable architecture, self-service tooling, and close collaboration across the company in a remote-first environment with in-person sessions as needed.

Qualifications

• 6+ years of software engineering experience.
• Experience building backend services and APIs.
• Experience with distributed systems or large scale data processing.
• Experience with ML platforms including training pipelines, model serving, feature pipelines.
• Proficiency in Python, Kotlin, Databricks, and AWS.
• Growth mindset and ability to translate complex requirements for multiple partners.

Responsibilities

• Build and optimize ML and simulation platform for increased scale and decisioning confidence.
• Develop software to apply ML models to evolving business needs.
• Create self-service tooling for feature registration and model deployment.
• Provide data and feature infrastructure, storage, serving, and online parity.
• Contribute to simulation systems reflecting production environments and reduce costs.
• Collaborate with ML, Engineering, Product, and Data teams; communicate progress.
• Mentor engineers on distributed systems, MLOps, and scalable architecture.

Skills

Python

Kotlin

Databricks

AWS

Distributed systems

ML platform

Spark

GCP/Azure

APIs

Tools

Metaflow

MLflow

gRPC

Spark/PySpark

dbt

Ray

GPU

Job description

Upstart is seeking a Senior Software Engineer for the ML and Simulations Platform to build an MLOps stack and a marketplace simulation layer. You will own backend services, feature pipelines, and model deployment, partnering with ML, Data, and Product teams to accelerate AI-driven decisions.

The role emphasizes scalable architecture, self-service tooling, and close collaboration across the company in a remote-first environment with in-person sessions as needed.