Senior Software Engineer - Machine Learning Platform

Role overview This senior engineering role sits on a Machine Learning and Simulations Platform team at an AI-driven lending marketplace, owning the infrastructure that powers underwriting, fraud, conversion, and verification models in production. The work spans low-latency and GPU model serving, self-service deployment tooling, a unified feature platform, and high-fidelity marketplace simulation. It is a remote-first position collaborating with ML, engineering, product, and data platform partners.

Responsibilities - Build and maintain the next-generation machine learning platform, optimizing scale, performance, and decision-time confidence. - Develop self-service tooling so ML teams can register features and deploy models independently, reducing manual platform work. - Design and contribute to simulation systems that more accurately reflect production environments and support experimentation. - Deliver the data and feature infrastructure for every model, including definition, storage, serving, and offline-to-online parity. - Partner with ML, engineering, product, and data teams to align roadmaps and keep stakeholders informed on platform initiatives. - Mentor engineers on distributed systems, MLOps, and scalable architecture across the team.

Requirements - Six or more years of software engineering experience with backend services and APIs. - Background in distributed systems or large-scale data processing using Spark, Databricks, Ray, or comparable tools. - Hands-on experience with machine learning infrastructure, model serving, or MLOps tooling. - Strong quantitative reasoning skills with an interest in working at the intersection of engineering and machine learning. - Excellent written and verbal communication skills with partners, peers, and product owners. - Self-directed work style balanced with collaborative team contribution.

Nice to have - Familiarity with Metaflow, MLflow, gRPC, Spark/PySpark, dbt, Ray, or GPU-based serving. - Knowledge of simulation, experimentation, or backtesting systems. - Experience building self-serve or configuration-driven tooling for internal users.

Benefits and work setup - Remote-first work with optional in-person collaboration through team onsites. - Base compensation range of $166,900 to $230,000 USD, plus bonus and equity components. - Comprehensive health coverage, retirement contributions with company match, ESPP eligibility, paid time off, parental leave, wellness and productivity allowances, and EAP access.