Senior Machine Learning Engineer
Attain · Chicago, IL
About this role
**Senior Machine Learning Engineer** **About the Role** Attain is seeking a Senior Machine Learning Engineer to own production ML systems and build out the MLOps platform infrastructure powering our B2C financial services. This hands-on, infrastructure-first role focuses on designing, building, and operating pipelines, platforms, and tooling that take models from experiment to reliable production service. **What You'll Do** • Build, deploy, and operate production ML systems with focus on reliability and performance • Own the production side of the model lifecycle: feature pipelines, deployment, CI/CD, monitoring, and retraining • Build reusable modeling pipelines, feature engineering systems, and model-serving infrastructure in GCP + Kubernetes • Instrument models with monitoring, alerting, and automated retraining using Prometheus/Grafana • Direct AI coding agents to write, test, and ship infrastructure code with strong judgment • Automate manual steps in the ML lifecycle to improve team velocity • Partner with data scientists to enable fast, safe model deployment and iteration • Collaborate across analysts, platform engineers, product managers, and stakeholders **Key Requirements** • 5+ years building and operating production ML systems • Strong expertise in model serving, monitoring, and production operations • Hands-on MLOps experience: pipelines, CI/CD, Docker, Kubernetes, Terraform, Airflow • Experience with low-latency online serving (gRPC/microservices, Istio) • Proficiency directing AI coding agents (Claude Code, Cursor, etc.) • Strong Python skills; systems/backend language experience (Go, Rust) a plus • SQL expertise and cloud data warehouse experience (BigQuery preferred) • Experience with distributed computing (Spark, Ray, Dask) • GCP experience preferred **Location** Chicago, IL | 4 days in-office, 1 day remote **Nice to Have** • STEM degree (CS, Statistics, Mathematics, Engineering, Physics, OR) • Background in credit decisioning, fraud, churn, or risk modeling • Model explainability and compliance experience in regulated decisioning • Observability tools experience (Prometheus, Grafana, Datadog)
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