IN_Senior Associate_Pega Developer _GCC_Advisory_Bangalore

PwC International

Bengaluru

On-site

INR 2,500,000 - 4,000,000

Full time

3 days ago

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Job summary

PwC is seeking an experienced Senior Associate in Bengaluru to drive data analytics, ML pipelines, and large language model solutions for clients. You will leverage Python, SQL, and modern ML frameworks to extract insights from complex data and enable data-driven decisions.

The role requires strong expertise in AI/ML tooling, cloud platforms, and DevOps practices, with 3+ years of experience and relevant certifications preferred.

Qualifications

3+ years of experience in data/AI engineering or related roles.

Responsibilities

ML Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining.
LLM Serving and GPU Architecture: Deep knowledge of GPU architectures; distributed training and serving for large language models.
Model Fine-Tuning and Optimization: Expertise in fine-tuning; improve latency and accuracy; minimize training/resource needs.
DevOps and LLMOps Proficiency: Proficiency in Kubernetes, Docker, and container orchestration; knowledge of Flowise/Langflow/Langgraph.

Skills

Gen AI

LLM

Huggingface

Python

SQL

JavaScript

pytorch

tensorflow

Docker

Kubernetes

Langchain

Langgraph

Education

BE/B.Tech

MBA

MCA

Master of Business Administration

Tools

AWS

Azure

GCP

MLflow

SageMaker

Vertex AI

DeepSpeed

Flowise

Langflow

Langraph

Docker

Kubernetes

FluentD

Kibana

Grafana

Job description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate

Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. 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.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

Job Description & Summary

A Career with in.................................

Responsibilities

ML Pipeline Design: Design ML pipelines for experiment management, model management, feature management, and model retraining. Design APIs for model inferencing at scale. Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI.
LLM Serving and GPU Architecture: Possess deep knowledge of GPU architectures. Expertise in distributed training and serving of large language models. Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM.
Model Fine-Tuning and Optimization: Demonstrate proven expertise in model fine-tuning and optimization techniques. Achieve better latencies and accuracies in model results. Reduce training and resource requirements for fine-tuning LLM and LVM models.
DevOps and LLMOps Proficiency: Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph.

Skill Matrix LLM