Senior Machine Learning Engineer

Sourced from feeny.ai

Attain is hiring a Senior Machine Learning Engineer to own production ML systems and build MLOps platform infrastructure for Klover's B2C fintech products. The role is infrastructure-first, focused on pipelines, feature infrastructure, model serving, CI/CD, and observability. You will enable data scientists to deploy and iterate on models safely while keeping systems reliable, performant, and cost-effective. The position follows a hybrid schedule in Chicago with 4 days in-office and 1 day remote.

• Build, deploy, and operate production ML systems for the EWA product
• Build and improve pipelines and serving infrastructure for predictive models
• Own the production model lifecycle: feature pipelines, deployment, CI/CD, monitoring, and automated retraining
• Build reusable modeling pipelines and model-serving infrastructure deployed via Terraform and CI/CD on GCP + Kubernetes
• Instrument models and pipelines with monitoring, alerting, and automated retraining using Prometheus/Grafana
• Direct AI coding agents to write, test, and ship infrastructure and pipeline code
• Automate manual ML lifecycle steps to improve team velocity
• Partner with data scientists to provide fast, safe paths to deploy and retrain models
• Collaborate with analysts, platform engineers, product managers, and stakeholders

• 5+ years as a Machine Learning Engineer, ML Platform Engineer, MLOps Engineer, Applied Scientist, or similar role building production ML systems
• Strong expertise deploying, serving, monitoring, and operating ML models in production
• Experience with low-latency online model serving (e.g., gRPC/microservices, ideally Istio)
• Hands-on MLOps experience with pipelines, CI/CD for ML, Docker, Kubernetes, Terraform, and Airflow
• Experience with model versioning, reproducibility, and progressive rollout (shadow, canary, champion-challenger)
• Strong Python coding skills and strong SQL skills
• Experience with cloud data warehouses and operational databases (e.g., BigQuery, Spanner)
• Experience with observability tools such as Prometheus, Grafana, or Datadog
• Experience with cloud platforms, GCP preferred
• Strong written and verbal communication skills

• Degree in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, or Operations Research
• Experience with a systems or backend language such as Go or Rust
• Experience with distributed computing and GPU-accelerated workloads (e.g., Spark, Ray, Dask)
• Familiarity with model explainability, auditability, and compliance considerations in regulated decisioning
• Experience building infrastructure for credit decisioning, risk modeling, fraud, churn, or consumer behavior modeling