Responsibilities:
· Define and implement the technical MLOps strategy and roadmap for the position
· Serve as a technical leader and mentor for MLOps engineers.
· Design, build, and maintain scalable and reliable machine learning & CI/CD pipelines.
· Ensure the efficient deployment, monitoring & Governance of AI models in production.
· Collaborate with data scientists and engineers to optimize model performance and deployment.
· Establish and enforce best practices for MLOps, including version control, model governance, and monitoring.
· Evaluate and implement new MLOps tools and technologies.
Required Skills:
· Extensive experience in designing and implementing MLOps strategies and pipelines.
· Deep expertise in on-prem platforms and containerization technologies (e.g., Docker, Kubernetes).
· Strong proficiency in programming languages like Python and scripting languages.
· Experience with CI/CD & MLOps tools as well as different ML frameworks.
· Strong understanding of data engineering and software development principles.
· Excellent communication and technical documentation skills.
· Ability to work effectively in a complex and dynamic environment.
Desirable Skills:
· Experience with feature stores and model registries.
· Knowledge of data governance and compliance requirements.