Senior Software Engineer - Machine Learning Platform
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.
About the job
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.
Skills
Python, Kotlin, Databricks, AWS, Spark, Ray, Distributed Systems, MLOps, MLflow, Metaflow, gRPC, dbt, Gpu Computing, Feature Engineering, Model Serving
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