Senior MLOps Engineer — Production AI Platform Lead

BetMGM; Kentucky; On-site; USD 135,000 - 170,000; Full time

Benefits offered by this job

Medical, Dental, Vision, Life, and_Dis

401(k) with company match

Pre‑tax spending accounts including HE

Flexible paid time off

Professional development reimbursement

Employee resource groups

Swag, ticket giveaways, and more!

Job summary

BetMGM is seeking a Senior MLOps Engineer to own the path from trained models to production endpoints. You will build and operate a scalable ML platform on AWS (SageMaker) and Snowflake, focusing on latency, cost, and reliability for batch and real-time inference.

You'll implement feature stores, CI/CD for ML, drift and quality monitoring, and champion/challenger deployment patterns. This role expects a software‑engineering‑first mindset with on‑call responsibility, based in the United States

Qualifications

• BS or MS in CS, Math, Statistics, ML, or related field or equivalent practical experience.
• 5+ years shipping software in production with Python, Docker, Kubernetes, CI/CD.
• 3+ years operating ML in production with latency and cost budgets.
• AWS SageMaker, Snowflake, and ML operations tools experience.
• IaC experience with Terraform or equivalent.

Responsibilities

• Stand up and operate BetMGM’s ML platform on AWS and Snowflake with Terraform.
• Build self-service templates for end-to-end model deployment, including CI, drift monitoring, and pre-baked connectivity.
• Design and operate batch scoring pipelines and real-time inference paths with latency budgets.
• Own the feature store with online/offline parity.
• Implement CI/CD for ML, model versioning, and lineage from feature to deployed model.
• Monitor drift and data quality; respond to incidents with post-mortems.

Skills

Python

Docker

Kubernetes

CI/CD

Distributed systems debugging

SageMaker

Snowflake

Terraform

ML production

Education

BS or MS in CS/Math/Stats/ML or related

Tools

SageMaker

Snowflake

Terraform

Job description

BetMGM is seeking a Senior MLOps Engineer to own the path from trained models to production endpoints. You will build and operate a scalable ML platform on AWS (SageMaker) and Snowflake, focusing on latency, cost, and reliability for batch and real-time inference.

You'll implement feature stores, CI/CD for ML, drift and quality monitoring, and champion/challenger deployment patterns. This role expects a software‑engineering‑first mindset with on‑call responsibility, based in the United States