Staff Software Engineer, Machine Learning
Core
Lead end-to-end ML engineering initiatives to optimize the model lifecycle (build, validate, deploy, change) for a consumer fintech platform, ensuring models ship faster and behave predictably in production.
Role type
Staff Software Engineer, Machine Learning (Infrastructure)
Builds
Production ML systems including feature stores, model registries, serving proxies, and training/serving infrastructure for underwriting, fraud detection, and risk exposure.
Domain
Fintech / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
End-to-end ML system design, ML platform architecture, Python, SQL, JVM languages, model lifecycle management, technical direction, stakeholder leadership, AI tool fluency
Preferred skills
Financial services domain experience, model risk management, streaming/CDK, large-scale batch processing (Apache Beam/Spark), distributed training
Technologies
Google Cloud Kubernetes Engine, MongoDB, BigQuery, Apache Beam, Dataflow, dbt, Airflow, Python, JVM
Responsibilities
Own technical direction for the ML stack end-to-end; build tooling for training/serving consistency; design model lineage and versioning; enable reproducible datasets for data scientists; measure delivery metrics and prioritize improvements; partner with cross-functional teams (Engineering, Data Science, Risk, Marketing, Finance).
Seniority
Staff, hands-on IC with strategic scope