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Staff ML Ops Engineer - Albert Invent Corp
MLOps Engineer
Lead end‑to‑end ML operations, designing scalable pipelines on AWS, containerizing models with Docker, orchestrating with Kubernetes, and automating deployments via CI/CD while ensuring robust monitoring and reproducibility with MLflow.
About the role
Key Responsibilities
- Architect and maintain production‑grade ML pipelines on AWS, ensuring high availability and scalability.
- Containerize models using Docker and deploy them to Kubernetes clusters, managing rollouts and rollbacks.
- Implement CI/CD workflows for model training, testing, and deployment, integrating with Git, Jenkins, or GitHub Actions.
- Integrate MLflow for experiment tracking, model registry, and lineage management.
- Collaborate with data scientists to translate research prototypes into production‑ready services.
- Monitor model performance, set up alerts, and perform root‑cause analysis for drift or degradation.
Requirements
- 5+ years of experience in ML operations or related roles.
- Proficiency in Python, AWS services (SageMaker, ECS, EKS, S3), Docker, and Kubernetes.
- Hands‑on experience with CI/CD pipelines and MLflow.
- Strong understanding of MLOps best practices, security, and compliance.
- Excellent communication skills and ability to mentor junior engineers.
Skills
pythonmachine learningawsdockerkubernetescicdmlflow