Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Job Description & Summary

A career within Data & Analytics Services will provide you with the opportunity to help our clients leverage transformation to enhance their customer experiences.

Responsibilities:

Position Overview: ML Ops Lead

- Lead the full ML system lifecycle: from experimentation and model development to production deployment and ongoing monitoring.
- Design and build scalable, cloud-native MLOps pipelines for training, validation, deployment, and lifecycle management.
- Develop and manage ML infrastructure on Azure, with emphasis on Azure Kubernetes Service (AKS).
- Implement best practices for model versioning, CI/CD, observability, and reproducibility in ML workflows.
- Productionize ML models as robust, low-latency APIs and batch systems integrated into healthcare workflows.
- Collaborate cross-functionally with data scientists, engineers,



and stakeholders to deliver scalable ML systems.
- Monitor model performance, detect drift, and ensure continuous model improvement in production.
- Mentor teams on MLOps practices, cloud engineering, and designing production-grade ML systems.
- Stay up-to-date with evolving trends in MLOps, distributed systems, and the Azure AI ecosystem.

Who We Are Looking For:

- 8+ years of experience in Machine Learning Engineering, MLOps, Data Science, or related quantitative fields.
- Strong background in machine learning complemented by software engineering skills and systems thinking for production deployments.
- Proven experience with large-scale, high-dimensional datasets and building scalable, reliable ML pipelines.
- Expertise with up-to-date ML methods, including Transformers for NLP and representation learning.
- Demonstrated success taking models from experimentation through to production using MLOps best practices (CI/CD, automation, orchestration).
- Ability to independently own ambiguous problems and deliver end-to-end ML solutions.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 IN_Manager_ML Ops Lead_Data and Analytics_Advisory_Hyderabad (Telangana)
🏢 PwC Service Delivery Center
📍 Telangana