Software Engineer II – Machine Learning

## About the Role The Senior Software Engineer on the Machine Learning and Simulations Platform team will build and operate the core infrastructure that supports machine learning model training, feature engineering, inference, model deployment, observability, and marketplace simulation. The role focuses on developing scalable MLOps capabilities that enable ML teams to move models into production efficiently and reliably. You will work across distributed systems, machine learning infrastructure, feature platforms, model serving, self-service tooling, and simulation systems. The role involves close collaboration with ML, Engineering, Product, and Data Platform teams while contributing to scalable architecture and mentoring other engineers. ## Key Responsibilities * Build, maintain, and optimize the machine learning and simulation platform for scale, performance, and reliable decisioning. * Develop high-quality backend software applications that enable machine learning models to support evolving business requirements. * Build self-service tooling that allows ML teams to register features and deploy models independently. * Reduce manual platform operations through automation and scalable tooling. * Develop data and feature infrastructure supporting model feature definition, storage, serving, and offline-to-online parity. * Design and contribute to simulation systems that accurately represent production environments. * Improve simulation efficiency and enable broader usage across ML and Finance teams. * Support machine learning model inference, process automation, model deployment, and observability through MLOps infrastructure. * Collaborate closely with ML, Engineering, Product, and Data Engineering teams. * Communicate requirements, progress, and technical considerations clearly with cross-functional stakeholders. * Mentor engineers and share expertise in distributed systems, MLOps, and scalable software architecture. ## Required Qualifications * 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 an equivalent technology. * Experience with an ML platform or machine learning production path, such as: * Training pipelines * Model serving * Feature pipelines * Training data platforms * Proficiency with some or many of the following: * Python * Kotlin * Databricks * AWS * Ability to learn and adopt new technologies based on project requirements. * Ability to understand complex requirements from ML, product, and engineering leadership and translate them for technical and non-technical stakeholders. ## Preferred Qualifications * Experience with Metaflow, MLflow, gRPC, Spark/PySpark, dbt, Ray, or GPU technologies. * Knowledge of simulation, experimentation, or backtesting systems. * Experience building self-service or configuration-driven tools for internal users. * Strong quantitative reasoning skills and interest in the intersection of software engineering and machine learning. * Strong ownership and accountability for quality and timely delivery. * Excellent written and verbal communication skills. * Ability to work effectively in both self-directed and collaborative environments. ## Technical Areas * Machine Learning Platform * MLOps * Machine Learning Infrastructure * Model Training and Inference * Model Serving * Feature Engineering and Feature Platforms * Distributed Systems * Large-Scale Data Processing * Backend Software Engineering * APIs * Data Platforms * Marketplace Simulation * Process Automation * Observability * Cloud Infrastructure * AWS * Spark / PySpark * Databricks * Ray * Python * Kotlin ## Work Arrangement * Remote * Location: United States * Team operates across East Coast and West Coast time zones. * Digital-first work environment. * Employees are encouraged to participate in regular in-person team onsites, generally once or twice per quarter for 2–4 consecutive days, depending on the team and role. ## Compensation & Benefits * Anticipated base salary range: $166,900–$230,000 * Target bonus * Equity compensation * Medical, dental, and vision benefits * 401(k) * Compensation may vary based on geographic location, job-related skills, experience, and relevant education or training. ## Apply Now Apply now for the Senior Software Engineer – Machine Learning Platform opportunity to build scalable MLOps, machine learning infrastructure, feature platforms, model serving, and simulation systems.