Senior ML Production Platform Engineer

BetMGM; Nevada (IA); On-site; USD 135,000 - 170,000; Full time

Benefits offered by this job

Medical, Dental, Vision, Life, and Dis

Disability Insurance

401(k) with company match

Pre‑tax spending accounts including H3

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 treat ML systems as software and own the path from training to production endpoints. You will balance latency, cost, and reliability across batch and real‑time inference on AWS SageMaker and Snowflake Cortex pipelines.

The role requires a strong software‑engineering mindset, experience with CI/CD for ML, feature stores, and drift/monitoring. GenAI integration is a plus, and collaboration with data scientists and engineers is essential.

Qualifications

• BS or MS in Computer Science, Math, Statistics, Machine Learning, or other STEM field; practical experience is valued.
• 5+ years shipping software in production with Python, Docker, Kubernetes or ECS, CI/CD, and distributed systems debugging.
• 3+ years operating ML in production with real traffic and defined latency/cost budgets.
• AWS SageMaker depth (Training, Endpoints, Batch Transform, Model Registry, Pipelines) and supporting services.
• Snowflake fluency (Snowpark ML, Cortex, dbt‑orchestrated batch scoring).
• IaC for ML (Terraform + SageMaker Pipelines or equivalent).
• Experience with feature stores (SageMaker Feature Store, Tecton, Feast) and online/offline parity.
• Champion/challenger, shadow, and canary deployment patterns as standard platform capabilities.
• Drift/monitoring tools (Evidently, Arize, SageMaker Model Monitor) integrated with paging.

Responsibilities

• Stand up and operate BetMGM’s ML platform on AWS and Snowflake with Terraform‑managed infra.
• Build self‑service scaffolds for end‑to‑end model deployment with CI, drift monitoring, alerting, and connectivity baked in.
• Design and operate batch scoring pipelines (SageMaker Batch Transform, dbt‑orchestrated scoring) and real‑time inference paths (SageMaker endpoints, Lambda + Bedrock).
• Own the feature store with online/offline parity; treat training‑serving skew as an incident.
• Implement CI/CD for ML: model registry, retraining triggers, and lineage from features to deployed models to live predictions.
• Support drift detection, data quality, and model performance monitoring with paging to humans; own incident response.
• Integrate GenAI (Bedrock, Anthropic, OpenAI) into production paths when applicable.
• Collaborate with data engineers, scientists, and partners across BetMGM and external vendors on standards and interfaces.

Skills

Python

Docker

Kubernetes/ECS

CI/CD

Distributed systems debugging

On-call

Education

BS or MS in Computer Science/Math/Statistics/Machine Learning

Tools

SageMaker

Snowflake

Terraform

Snowpark ML

Cortex

Bedrock

Lambda

S3

Job description

BetMGM is seeking a Senior MLOps Engineer to treat ML systems as software and own the path from training to production endpoints. You will balance latency, cost, and reliability across batch and real‑time inference on AWS SageMaker and Snowflake Cortex pipelines.

The role requires a strong software‑engineering mindset, experience with CI/CD for ML, feature stores, and drift/monitoring. GenAI integration is a plus, and collaboration with data scientists and engineers is essential.