LLMOps + MLOps - Associate 2

PwC Acceleration Center India; Bengaluru; Presencial; INR 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

PwC Acceleration Center India is seeking an Associate to support LLMOps and MLOps tasks, building ML pipelines and automating model workflows. The role involves collaborating across teams, documenting processes, and applying ML methods to client projects.

Ideal candidates have a bachelor’s degree and strong English communication, with exposure to Python, SQL, and cloud platforms. This is a hands-on, fast-paced role at PwC’s global delivery center in India.

Formación

• Bachelor's degree required or equivalent.
• Proficiency in English (oral and written) required.

Responsabilidades

• Support LLMOps and MLOps activities across data science initiatives.
• Build and maintain ML pipelines for development, testing, deployment, and monitoring.
• Automate workflow steps using cloud-based tools and platforms.
• Collaborate with technical teams to translate requirements into model support tasks.
• Document model inputs, outputs, dependencies, and run procedures for repeatable execution.
• Analyze model performance data and identify issues affecting reliability or data quality.
• Apply statistical analysis and ML concepts to troubleshoot model behavior.
• Contribute to data preparation, feature creation, and data pipeline activities.
• Support NLP, deep learning, and predictive modeling work across client projects.
• Learn new tools and methods quickly while owning deliverables and timelines.

Conocimientos

Python

SQL

NLP

ML Concepts

Data Pipelines

Educación

Bachelor's degree

Herramientas

Cloud Platforms

Descripción del empleo

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-solver 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 an LLMOps + MLOps Associate, you will support the design, development, deployment, and ongoing improvement of data science solutions that help turn data into actionable insights and support informed decision-making within our Data and Analytics Engineering practice. As an Associate you will contribute to project tasks, build technical skills through hands-on learning, adapt to changing client needs, and develop a deeper understanding of how your work supports broader team goals. In this role at PwC Acceleration Center India, you will work across LLMOps and MLOps activities, assist with exploratory analysis and statistical modeling, and help create data visualizations and machine learning workflows that support client support delivery in a fast-paced environment.

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 You Must Have

• At least a Bachelor's degree
• 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
• 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