remote
MLOps Engineer - dv01
MLOps Engineer
Lead the deployment and scaling of machine learning models in a high‑volume structured finance environment, leveraging Python, Docker, Kubernetes, and AWS to build robust, reproducible MLOps pipelines.
About the role
Key Responsibilities
- Design, implement, and maintain end‑to‑end MLOps pipelines for production‑grade machine learning models.
- Containerize models with Docker and orchestrate deployments on Kubernetes clusters.
- Integrate CI/CD workflows using GitHub Actions, Jenkins, or similar tools to automate testing, validation, and rollout.
- Collaborate with data scientists to translate research prototypes into scalable, production‑ready services.
- Monitor model performance, drift, and resource utilization; implement automated alerts and remediation.
- Ensure compliance with security, governance, and regulatory requirements for financial data.
Requirements
- 3+ years of experience in MLOps or related roles within data‑centric organizations.
- Experience with model monitoring, logging, and observability tools.
- Excellent problem‑solving skills and ability to work cross‑functionally in a fast‑paced environment.
Skills
pythonmachine learningmlopsdockerkubernetesawscicd