Senior MLOps Engineer

Talent; Chicago (IL); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Talent, a fintech leader, is seeking a Senior MLOps Engineer to join its growing ML team in a hybrid role (3 days onsite). You'll build and scale cloud-native MLOps infrastructure that enables data scientists to deploy real-time models into production, working with data science, engineering, and product teams.

Ideal candidates have 5+ years in MLOps/ML engineering, hands-on AWS, Docker, Kubernetes, CI/CD, and experience with MLflow or Kubeflow.

Tools

AWS

Docker

Kubernetes

CI/CD

MLflow

Kubeflow

Spark

Hadoop/Cloudera

Scala/Java

Job description

I'm partnering with an established fintech organization that is looking to add a Senior MLOps Engineer to its growing Machine Learning team.

Location: Hybrid (3 days/week onsite) – Candidates must be located in or willing to commute to one of the following:

• Scottsdale, AZ
• Chicago, IL
• New York, NY

In this role, you'll build and scale cloud-native MLOps infrastructure that enables data scientists to deploy real-time machine learning models into production. You'll collaborate with Data Science, Engineering, and Product teams to automate the machine learning lifecycle, optimize model performance, and deliver scalable AI solutions.

What they're looking for:

• 5+ years of experience in MLOps, ML Engineering, or Data Science
• Hands-on experience with AWS, Docker, Kubernetes, and CI/CD
• Experience with MLflow, Kubeflow, or similar MLOps platforms
• Background deploying production ML models at scale
• Experience with Spark, Hadoop/Cloudera, or Scala/Java is a plus