# Senior Software Engineer - Machine Learning Platform

**Company:** [Upstart](https://hotfix.jobs/companies/upstart)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $167k – $230k/yr
**Experience:** 6+ years
**Skills:** Python, Kotlin, Databricks, AWS, Spark, Ray, Distributed Systems, MLOps, MLflow, Metaflow, gRPC, dbt, Gpu Computing, Feature Engineering, Model Serving
**Posted:** 2026-08-27

> Build and operate backend infrastructure for machine learning model training, serving, feature management, and marketplace simulation. The role requires 6+ years of software engineering experience, distributed systems expertise, and experience with production ML platforms.

## Job Description

## Responsibilities
- Build, maintain, and optimize a machine learning and simulation platform for scale, performance, and confidence in decisioning.
- Develop backend software applications and APIs that apply machine learning models to evolving business needs.
- Build self-service tooling for ML teams to register features and deploy models independently.
- Develop feature infrastructure covering feature definition, storage, serving, and offline-to-online parity.
- Design and contribute to simulation systems that reflect production environments, reduce simulation costs, and broaden usage.
- Collaborate with ML, Engineering, Product, and Data Engineering teams.
- Mentor engineers on distributed systems, MLOps, and scalable architecture.

## Requirements
- 6+ years of software engineering experience.
- Experience building and maintaining backend software services and APIs.
- Experience with distributed systems or large-scale data processing using Spark, Databricks, Ray, or equivalent technologies.
- Experience with an ML platform or production ML workflows, such as training pipelines, model serving, feature pipelines, or training data platforms.
- Proficiency with some or many of Python, Kotlin, Databricks, and AWS.
- Ability to understand complex requirements and communicate them to technical and non-technical partners.

## Nice-to-haves
- Metaflow, MLflow, gRPC, Spark/PySpark, dbt, Ray, or GPU experience.
- Knowledge of simulation, experimentation, or backtesting systems.
- Experience building self-service or configuration-driven internal tooling.
- Strong quantitative reasoning and interest in engineering and machine learning.
- Strong ownership, accountability, written communication, and verbal communication skills.
- Ability to work effectively in self-directed and collaborative environments.

## Compensation and Benefits
- Anticipated base salary: $166,900–$230,000 USD, varying by geographic compensation region.
- Target bonuses, equity compensation, and annual equity grants.
- Medical, dental, vision, wellness, retirement, paid time off, sick leave, company holidays, family and parental leave, life insurance, and disability coverage.
- 401(k) or Group Retirement Savings Plan match and an Employee Stock Purchase Plan for eligible employees.

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