Senior MLOps Engineer — Build Production ML Platform

BetMGM; New York (NY); On-site; USD 135,000 - 170,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Pre‑tax accounts

Flexible PTO

Professional development

Employee resource groups

Swag & ticket giveaways

Job summary

BetMGM in New York seeks a Senior MLOps Engineer to own its production ML platform, including feature store, model registry, and CI/CD for ML. You will ship models from data science to live endpoints with strong latency, cost, and reliability budgets across batch and real‑time paths.

Expertise in SageMaker, Snowflake, Terraform, and observability is required, with GenAI familiarity a plus. Collaboration with data teams and partners is essential.

Qualifications

• BS or MS in Computer Science, Math, Statistics, ML, or related field; practical experience acceptable.
• 5+ years shipping software in production with on-call duties and distributed systems knowledge.
• 3+ years operating ML in production with latency and cost budgets.

Responsibilities

• Stand up and operate BetMGM’s ML platform on AWS and Snowflake with IaC.
• Design batch and real-time inference paths with latency targets and cost limits.
• Own feature store parity and model registry lifecycle across environments.
• Implement CI/CD for ML models including retraining triggers and versioning.
• Monitor drift, data quality, and model performance; manage incident response.

Skills

Python

Docker

Kubernetes

CI/CD

Distributed systems debugging

On-call experience

AWS SageMaker

Snowflake/Cortex

Terraform IaC

ML platform ownership

Education

BS or MS in CS/Math/Stats/ML

Tools

SageMaker

Snowflake

Terraform

Job description

BetMGM in New York seeks a Senior MLOps Engineer to own its production ML platform, including feature store, model registry, and CI/CD for ML. You will ship models from data science to live endpoints with strong latency, cost, and reliability budgets across batch and real‑time paths.

Expertise in SageMaker, Snowflake, Terraform, and observability is required, with GenAI familiarity a plus. Collaboration with data teams and partners is essential.