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MLOps Engineer - Booksy
MLOps Engineer
Senior MLOps Engineer building a scalable ML platform from scratch, integrating model training, deployment, and monitoring using Python, Docker, Kubernetes, and AWS services.
About the role
Key Responsibilities
- Design, develop, and maintain end‑to‑end ML pipelines for training, validation, and production deployment.
- Implement CI/CD workflows for model versioning, containerization, and automated testing.
- Collaborate with data scientists to translate research prototypes into robust, scalable services.
- Monitor model performance in production, set up alerting, and drive continuous improvement.
- Manage cloud infrastructure (AWS) and orchestrate workloads with Kubernetes.
Requirements
- 5+ years of experience in ML engineering or MLOps roles.
- Hands‑on experience with AWS services (SageMaker, ECS/EKS, S3, CloudWatch).
- Strong understanding of model lifecycle management, monitoring, and observability.
- Excellent problem‑solving skills and a collaborative mindset.
Skills
pythonmachine learningmlopsdockerkubernetescicdaws