Industry/Sector

Specialism

Management Level

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a 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 within our Data and Analytics Engineering practice. As a Manager you will motivate and develop team members, direct project workstreams, and use sound judgment to guide delivery, coaching others to build skills while supporting client expectations. In this role at PwC, you will help translate advanced analytics, statistical modeling, and data visualization into practical solutions for complex business challenges, while supporting work across cloud engineering, data, analytics, and AI capabilities at PwC Acceleration Center India.

Responsibilities

- Leading LLMOps and MLOps workstreams across model lifecycle planning, deployment, monitoring, and retraining
- Managing client-facing data science engagements and aligning delivery plans with project scope, timelines, and budget
- Guiding teams in building machine learning pipelines, data models, and automated workflows for AI-driven solutions
- Reviewing technical deliverables for model performance, data quality, and operational readiness across production environments
- Applying cloud engineering and analytics tools to scale machine learning systems and improve deployment repeatability
- Coaching team members on AI fluency, data science methods, and troubleshooting approaches for complex implementation issues
- Translating business needs into practical machine learning solutions that support decision-making and operational improvement
- Identifying opportunities to refine model monitoring, orchestration, and lifecycle management practices across client projects
- Developing documentation and technical recommendations that support adoption of machine learning and generative AI capabilities
- Collaborating with technology and business stakeholders to address risks, dependencies, and delivery challenges

What You Must Have

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

What Sets You Apart

- 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, 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

Travel Requirements

Job Posting End Date