BetMGM LLC

Senior Machine Learning Operations Engineer

NJ, US$135,000-$170,000Posted 2 months ago

Job Description

Discover What’s Possible at BetMGM

Ready to make your career legendary? Join us as we bring the magic of Vegas to our players. The BetMGM team has over 1,400 talented members, revolutionizing sports betting and online gaming in the United States and Canada. We’re a brand with technology at our hearts and the most driven and focused talent in the business.

As a valued team member, we’re committed to giving you the resources and support you need to thrive. Our benefits and perks include:

  • Medical, Dental, Vision, Life, and Disability Insurance
  • 401(k) with company match
  • Pre-tax spending accounts including health care FSA and commuter savings
  • Flexible paid time off
  • Professional development reimbursement and ongoing skills training opportunities
  • Employee resource groups
  • Swag, ticket giveaways, and more!

At BetMGM, we recognize that every individual plays a meaningful role in our success. That’s why we’re committed to building a respectful, inclusive workplace. It’s the strategy behind every win. By meeting people where they are, we create a culture of belonging where everyone can thrive and a workplace that reflects our values, our people, and our drive to win.

About the Role

The Senior MLOps Engineer treats ML systems as software systems and owns the path from a trained model to a production endpoint that meets its latency, cost, and reliability budgets — across both batch scoring (SageMaker Batch Transform, Snowflake Cortex / Snowpark ML, dbt-orchestrated scoring) and real-time inference (SageMaker real-time endpoints, Lambda + Bedrock, sub-second feature serving). The Senior Engineer builds the platform that data scientists and ML engineers ship on: feature store with guaranteed online/offline parity, model registry, CI/CD for ML, drift and quality monitoring, champion/challenger and shadow deployment scaffolding. This requires a software-engineering-first mindset — distributed systems, observability, and on

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