onsite
Senior Machine Learning Operations Engineer - BetMGM
ML Engineer
Lead end‑to‑end ML operations, building scalable pipelines on AWS, Docker, and Kubernetes, while automating model deployment and monitoring with CI/CD practices.
About the role
Key Responsibilities
- Design, develop, and maintain production‑grade ML pipelines using Python and AWS services (SageMaker, ECS, EKS).
- Containerize models with Docker, orchestrate deployments on Kubernetes, and manage scaling and resilience.
- Implement CI/CD workflows for model training, testing, and deployment, ensuring rapid, reliable releases.
- Monitor model performance, set up alerting, and perform root‑cause analysis to maintain high availability.
- Collaborate with data scientists, data engineers, and product teams to translate research into production solutions.
Requirements
- 5+ years of experience in ML Ops or related roles.
- Proficiency in Python, Docker, Kubernetes, and AWS.
- Strong understanding of CI/CD pipelines and automated testing.
- Experience with model monitoring, logging, and alerting tools.
- Excellent problem‑solving skills and a collaborative mindset.
Skills
pythonmachine learningawsdockerkubernetescicd