Senior ML Production Platform Engineer

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

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

401(k) with company match

Pre‑tax spending accounts

Flexible PTO

Professional development reimbursement

Employee resource groups

Ticket giveaways

Job summary

BetMGM is seeking an experienced Senior MLOps Engineer to own the path from model to production. You will build a production‑grade ML platform on AWS SageMaker and Snowflake, with feature stores, CI/CD, and scalable endpoints for batch and real‑time inference.

You’ll implement drift and quality monitoring, cost controls, and deployment patterns while collaborating with data scientists and engineers to ship reliable models at scale.

Qualifications

• BS or MS in CS, Math, Statistics, ML, or equivalent practical experience.
• 5+ years shipping software in production with Python, Docker, Kubernetes/ECS, CI/CD and on-call.
• 3+ years operating ML in production with latency and cost budgets.
• AWS SageMaker depth (Training, Endpoints, Batch Transform, Model Registry, Pipelines).
• Snowflake fluency with Snowpark ML, Cortex, dbt‑orchestrated scoring.
• IaC for ML with Terraform + SageMaker Pipelines.
• Feature store ownership with online/offline parity.
• Champion/challenger and canary deployment patterns.

Responsibilities

• Stand up and operate BetMGM’s ML platform on AWS SageMaker and Snowflake with Terraform‑managed infrastructure.
• Build self‑service scaffolds for data scientists to ship models end‑to‑end.
• Design batch scoring pipelines with cost/latency SLAs.
• Design real‑time inference paths with sub‑100ms latency budgets and graceful degradation.
• Own the feature store with online/offline parity; manage drift and monitoring.
• Implement CI/CD for ML including model registry, retraining triggers, and lineage.
• Establish deployment patterns like champion/challenger and canary releases.
• Set up drift detection, data quality, and model performance monitoring with paging.

Skills

5+ years production software

3+ years ML in production

Python

Docker

Kubernetes/ECS

CI/CD

Distributed systems debugging

On-call experience

AWS SageMaker

Snowflake Snowpark ML

Model monitoring

GenAI integration (nice-to-have)

Education

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

Tools

Terraform

Snowflake

Job description

BetMGM is seeking an experienced Senior MLOps Engineer to own the path from model to production. You will build a production‑grade ML platform on AWS SageMaker and Snowflake, with feature stores, CI/CD, and scalable endpoints for batch and real‑time inference.

You’ll implement drift and quality monitoring, cost controls, and deployment patterns while collaborating with data scientists and engineers to ship reliable models at scale.