MLOps Lead

This role focuses on leading and managing the development, deployment, and maintenance of machine learning models and pipelines. The MLOps Lead will be responsible for ensuring the reliability, scalability, and efficiency of the ML infrastructure, collaborating closely with data scientists, engineers, and other stakeholders to deliver high-quality machine learning solutions.

Key Responsibilities:

Lead the design, implementation, and maintenance of MLOps platforms and tools.
Develop and enforce best practices for model deployment, monitoring, and versioning.
Automate ML workflows to improve efficiency and reduce manual intervention.
Collaborate with data scientists to optimize models for production environments.
Troubleshoot and resolve issues related to ML infrastructure and pipelines.
Ensure the security and compliance of ML systems.
Mentor and guide junior MLOps engineers.

Requirements/Qualifications:

Extensive experience in machine learning operations (MLOps).
Strong understanding of DevOps principles and practices.
Proficiency in cloud platforms (e.g., AWS, Azure, GCP).
Experience with containerization technologies (e.g., Docker, Kubernetes).
Familiarity with CI/CD pipelines for ML models.
Excellent communication and collaboration skills.
Proven ability to lead and manage technical teams.
9 to 14 years of relevant experience.

About the Company: Capgemini is a global leader in technology services and digital transformation. They help organizations navigate their digital journeys, providing a wide range of consulting, technology, and outsourcing services.