Senior ML Engineer - Production ML & MLOps (Hybrid)

Attain; Chicago (IL); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Attain in Chicago seeks a Senior Machine Learning Engineer to own production ML systems and build our MLOps platform infrastructure across our app portfolio. This hands-on, infrastructure-first role focuses on reliable pipelines, scalable feature stores, and cost-effective model serving in production.

You will work with data scientists and platform engineers to deploy, monitor, retrain, and improve models, while keeping systems secure, observable, and fast in a hybrid office setting (4 days

Qualifications

• 5+ years of direct experience as ML engineer or similar role.
• Strong background in deploying ML models to production.
• Experience with low-latency online model serving (e.g., gRPC) for real-time decisioning.
• Hands-on MLOps: CI/CD for ML, containerization (Docker), orchestration (Kubernetes), infrastructure-as-code (Terraform).
• Experience with model versioning, reproducibility, and safe progressive rollout of models in production.
• Demonstrated ability to direct AI coding agents to build, operate, and debug ML systems.
• Strong software and platform engineering fundamentals.
• Experience with distributed computing and GPU-accelerated workloads.
• Strong SQL skills and cloud data warehouses (e.g., BigQuery)

Responsibilities

• Build, deploy, and operate the production ML systems at the core of our platform with emphasis on reliability and performance.
• Develop and enhance pipelines and serving infrastructure behind predictive models across decisioning, fraud, churn, and revenue use cases.
• Own the production side of the model lifecycle: feature pipelines, deployment, CI/CD, monitoring, retraining.
• Create reusable modeling pipelines and production-grade code deployed via Terraform and CI/CD into GCP and Kubernetes.
• Instrument models with monitoring, alerting, and automated retraining; surface drift and degradation metrics.
• Direct AI coding agents to write, test, and ship infrastructure and pipeline code with verification.
• Automate repetitive ML workflows to accelerate delivery without sacrificing reliability.
• Collaborate with data scientists to enable fast, safe model deployment and iteration.
• Work with analysts, platform engineers, product managers, and stakeholders to ensure quality and efficiency.
• Identify platform improvements and tooling to boost product velocity and outcomes.

Skills

Production ML

MLOps

Python

Go/Rust

CI/CD for ML

Terraform

Kubernetes

Data analysis

Communication

Education

Bachelor's or higher in CS/Math/Engineering

Tools

Docker

Kubernetes

Terraform

Airflow

Prometheus

Grafana

BigQuery

GCP

Job description

Attain in Chicago seeks a Senior Machine Learning Engineer to own production ML systems and build our MLOps platform infrastructure across our app portfolio. This hands-on, infrastructure-first role focuses on reliable pipelines, scalable feature stores, and cost-effective model serving in production.

You will work with data scientists and platform engineers to deploy, monitor, retrain, and improve models, while keeping systems secure, observable, and fast in a hybrid office setting (4 days