# Senior Manager, Software Engineering - Machine Learning Simulations

**Company:** [Upstart](https://hotfix.jobs/companies/upstart)
**Location:** Remote
**Role:** Engineering Management
**Salary:** $195k – $270k/yr
**Experience:** 8+ years
**Skills:** Python, Kotlin, AWS, Kubernetes, Databricks, Spark, Distributed Systems, MLOps, Model Inference, Workflow Orchestration, Data Pipelines, Backtesting
**Posted:** 2026-09-10

> Leads the team responsible for Upstart’s machine-learning simulation platform, driving roadmap, reliability, scalability, cost efficiency, and cross-functional adoption. Requires 8+ years of software engineering experience, including 3+ years managing engineering teams and experience with production backend platforms or distributed systems.

## Job Description

## Responsibilities
- Own the engineering roadmap for the marketplace simulation platform and prioritize teams and use cases.
- Lead, coach, and grow engineers working across distributed services, offline data pipelines, and large-scale compute.
- Improve simulation reliability and accuracy for launch decisions, including automated checks for drift between simulated and production results.
- Reduce simulation costs as usage grows through architecture and compute decisions.
- Extend simulation coverage across the lending funnel and new loan products in partnership with teams owning pricing and decisioning logic.
- Build self-service simulation workflows for machine learning, analytics, and capital markets partners.

## Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
- 8+ years of software engineering experience, including 3+ years of engineering management experience.
- Experience leading teams that build and operate backend platforms or distributed systems in production.
- Experience delivering platform or infrastructure programs spanning multiple teams.
- Proficiency with some or many of Python, Kotlin, AWS, Kubernetes, Databricks, and Spark.

## Nice-to-haves
- Knowledge of simulation, backtesting, experimentation, or offline model evaluation systems.
- Experience supporting machine learning teams or operating MLOps infrastructure, including model inference, workflow orchestration, and offline feature pipelines.
- Knowledge of lending, pricing, credit risk, or marketplace economics.
- Experience optimizing compute cost and efficiency alongside reliability.
- Experience building shared platforms with partner-owned logic and stable interfaces.
- Experience developing senior engineers and emerging engineering leaders.

## Compensation and Benefits
- Base salary range: $195,300–$270,400 USD.
- Target bonuses, equity compensation, annual equity grants, and competitive benefits.
- Retirement benefits with company matching, employee stock purchase plan, health coverage, income protection, paid time off, family and parental leave, wellness and productivity allowances, and financial wellness resources.

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