LLMOps + MLOps - Associate

PwC; Hyderabad, Chennai District, Bengaluru; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

PwC is hiring for an MLOps/Data Science support role in Hyderabad, focusing on building and maintaining ML pipelines for model development, testing, deployment and monitoring. You will automate workflow steps with cloud-based platforms, collaborate with cross-functional teams, and document run procedures and data dependencies.

Ideal candidates will have coursework or projects in ML/data science, knowledge of LLMOps/MLOps concepts, and practical experience using Python and SQL in academic or

Qualifications

• Demonstrating coursework or projects in machine learning and data science.
• Applying foundational knowledge of LLMOps or MLOps concepts.
• Using Python, SQL, or cloud tools in academic or project settings.
• Gathering and interpreting data from varied sources.

Responsibilities

• Supporting LLMOps and MLOps activities across data science and data engineering initiatives.
• Building and maintaining machine learning pipelines for model development, testing, deployment, and monitoring.
• Automating workflow steps using cloud-based tools and digital platforms to streamline model operations.
• Collaborating across technical teams to gather requirements and translate them into operational model support tasks.
• Documenting model inputs, outputs, dependencies, and run procedures to support repeatable execution.
• Analyzing model performance data and identifying issues that affect reliability, scalability, or data quality.
• Contributing to data preparation, feature creation, and data pipeline activities for analytics solutions.
• Supporting natural language processing, deep learning, and predictive modeling work across client projects.
• Learning new tools and methods quickly while taking ownership of assigned deliverables and timelines.

Skills

Python

SQL

ML concepts

Cloud tools

Education

Artificial Intelligence and Robotics

Business Analytics

Computer Science

Machine Learning

Job description

Responsibilities

• - Supporting LLMOps and MLOps activities across data science and data engineering initiatives
• - Building and maintaining machine learning pipelines for model development, testing, deployment, and monitoring
• - Automating workflow steps using cloud-based tools and digital platforms to streamline model operations
• - Collaborating across technical teams to gather requirements and translate them into operational model support tasks
• - Documenting model inputs, outputs, dependencies, and run procedures to support repeatable execution
• - Analyzing model performance data and identifying issues that affect reliability, scalability, or data quality
• - Applying statistical analysis, machine learning concepts, and programming skills to troubleshoot model behavior
• - Contributing to data preparation, feature creation, and data pipeline activities for analytics solutions
• - Supporting natural language processing, deep learning, and predictive modeling work across client projects
• - Learning new tools and methods quickly while taking ownership of assigned deliverables and timelines

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
• - Demonstrating coursework or projects in machine learning and data science
• - Applying foundational knowledge of LLMOps or MLOps concepts
• - Using Python, SQL, or cloud tools in academic or project settings
• - Gathering and interpreting data from varied sources
• - Communicating ideas clearly and adapting across team settings