mlops lead

Job Description MLOps Lead

Experience: 7–10 Years
Relevant Experience: Minimum 5 years in ML Engineering / MLOps
Role: MLOps Lead
Location: Bengaluru

Job Overview

We are seeking an experienced MLOps Lead with strong expertise in Python, machine learning engineering, model deployment, and production ML operations. The ideal candidate must have proven leadership experience and the ability to lead the development, deployment, monitoring, and automation of scalable machine learning solutions.

Key Responsibilities

• Lead the design, development, and implementation of end-to-end MLOps pipelines.
• Develop and maintain robust Python-based solutions for machine learning workflows and automation.
• Lead the deployment and operationalization of ML models in production environments.
• Design and implement CI/CD pipelines for automated model testing, validation, deployment, and release management.
• Establish model monitoring processes to track performance, model drift, reliability, and data quality.
• Manage and optimize cloud infrastructure supporting ML workloads.
• Automate model lifecycle management, including versioning, retraining, deployment, and monitoring.
• Collaborate with Data Scientists, ML Engineers, and DevOps teams to streamline ML delivery.
• Troubleshoot production issues and improve model serving performance, scalability, and reliability.
• Define MLOps best practices and provide technical guidance and mentorship to team members.

Mandatory Skills

• 7–10 years of overall experience.
• Minimum 5 years of relevant ML Engineering / MLOps experience.
• Proven leadership experience is mandatory.
• Strong proficiency in Python programming.
• Hands-on experience with machine learning model deployment and productionization.
• Strong experience building and managing ML pipelines.
• Expertise in CI/CD implementation and automation.
• Experience with model monitoring and ML lifecycle management.
• Knowledge of cloud infrastructure for ML workloads.

Preferred Skills

• Experience with MLflow or similar model lifecycle management tools.
• Familiarity with Docker and Kubernetes.
• Experience with cloud-based ML platforms such as Azure ML, AWS SageMaker, or Google Vertex AI.
• Understanding of model versioning, reproducibility, and model drift detection.

Ideal Candidate Profile

A hands-on MLOps professional with strong Python programming skills, at least five years of relevant ML experience, and proven leadership capabilities in deploying, monitoring, and managing production-grade machine learning systems.

Note: Leadership experience and strong Python skills are mandatory for this role.