LLMOps + MLOps - Manager

Overview

As an LLMOps + MLOps Manager, you will lead client support work in data science and data and analytics engineering, overseeing teams that design, develop, and refine machine learning and large language model operations solutions.

What you'll do

• Lead LLMOps and MLOps workstreams across model lifecycle planning, deployment, monitoring, and retraining.
• Manage client-facing data science engagements and align delivery plans with project scope, timelines, and budget.
• Guide teams in building machine learning pipelines, data models, and automated workflows for AI-driven solutions.
• Review technical deliverables for model performance, data quality, and operational readiness across production environments.
• Apply cloud engineering and analytics tools to scale machine learning systems and improve deployment repeatability.
• Coach team members on AI fluency, data science methods, and troubleshooting approaches for complex implementation issues.
• Translate business needs into practical machine learning solutions that support decision-making and operational improvement.
• Identify opportunities to refine model monitoring, orchestration, and lifecycle management practices across client projects.
• Develop documentation and technical recommendations that support adoption of machine learning and generative AI capabilities.
• Collaborate with technology and business stakeholders to address risks, dependencies, and delivery challenges.
• Motivate and develop team members, direct project workstreams, and guide delivery while supporting client expectations.

What you'll need

• At least a Bachelor's degree.
• At least 8 years of experience.
• Oral and written proficiency in English.

Nice to have

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, or Systems Engineering.
• Managing LLMOps and MLOps delivery across client engagements.
• Leading data science teams through planning, execution, and delivery.
• Applying machine learning, deep learning, and NLP techniques.
• Translating complex system interactions into clear delivery plans.
• Mentoring teammates while validating quality, timelines, and standards.

Details

• Location: Bangalore.