Senior MLOps Engineer: Build Production ML Pipelines

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

Benefits offered by this job

Medical insurance

401(k) with company match

Flexible paid time off

Professional development reimbursement

Employee resource groups

Swag and tickets

Job summary

BetMGM is seeking a Senior MLOps Engineer to own the production ML platform, delivering scalable, reliable inference and model lifecycle tooling. You will collaborate with data scientists to ship end-to-end ML solutions on AWS and Snowflake, with strong emphasis on CI/CD, monitoring, and cost control.

The role requires a software‑engineering mindset, on-call readiness, and familiarity with SageMaker, Snowflake, and Terraform. GenAI is a plus, not required.

Qualifications

• BS or MS in CS, Math, Stats, ML, or STEM; practical experience counts.
• 5+ years shipping production software; 3+ years ML in production.
• AWS SageMaker depth across Training, Endpoints, Batch Transform, Model Registry, Pipelines.
• Snowflake fluency with Snowpark ML, Cortex, and batch scoring.

Responsibilities

• Stand up and operate BetMGM’s ML platform on AWS and Snowflake with Terraform-managed infra.
• Build self-service scaffolds so data scientists ship end-to-end models without tickets.
• Design and run batch scoring pipelines with clear freshness and cost SLAs.
• Design and operate real-time inference paths with sub-100ms latency targets.
• Own feature stores with online/offline parity and trained model governance.
• Build CI/CD for ML: registry, retraining triggers, and lineage.
• Implement champion/challenger, shadow deployments and canary releases.
• Stand up drift detection, data quality, and model monitoring with paging.

Skills

Python

Docker

Kubernetes

CI/CD

AWS

SageMaker

Snowflake

Terraform

Observability

On-call

Education

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

Tools

SageMaker Training

SageMaker Endpoints

SageMaker Pipelines

Snowpark ML

Cortex

dbt

Terraform

SageMaker Feature Store

Job description

BetMGM is seeking a Senior MLOps Engineer to own the production ML platform, delivering scalable, reliable inference and model lifecycle tooling. You will collaborate with data scientists to ship end-to-end ML solutions on AWS and Snowflake, with strong emphasis on CI/CD, monitoring, and cost control.

The role requires a software‑engineering mindset, on-call readiness, and familiarity with SageMaker, Snowflake, and Terraform. GenAI is a plus, not required.