IN_Manager_AI Engineer_GCC_Advisory_Chennai

Price Waterhouse Cooper LLP; Chennai; Hybrid; INR 2,500,000 - 4,200,000; Full time

Job summary

Price Waterhouse Cooper LLP in India is seeking a Manager in Advisory for Data, Analytics & AI to design ML pipelines, manage experiments, and deploy models at scale across client engagements. You will leverage MLflow, SageMaker, Vertex AI and Azure AI, with GPUs and distributed training, to deliver data-driven insights and strategic outcomes for diverse industries.

Join a vibrant PwC data and analytics community, focused on innovation, collaboration, and delivering value through trusted

Qualifications

• Experience with ML/AI platforms and pipelines.
• Strong programming in Python and ML frameworks.
• Proficient in ML deployment tools (Docker, Kubernetes) and cloud AI services.

Responsibilities

• ML Pipeline Design: design ML pipelines for experiment management, model management, feature management, and model retraining.
• LLM Serving and GPU Architecture: knowledge of GPU architectures, distributed training and serving of large language models.
• DevOps and LLMOps Proficiency: expertise in Kubernetes, Docker, and container orchestration; familiarity with Flowise, Langflow, Langgraph.

Skills

Gen AI

LLM

Huggingface

python

pytorch/tensor flow/keras

Langchain

Langgraph

Docker

Kunernetes

Education

Bachelor of Technology

B.Tech/MCA/BCA/M.tech

Tools

Kubernetes

Docker

Job description

Job Description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

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 forour 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, flexibilityprogrammesand mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences foreach other. Learn moreabout us At PwC, we believe inprovidingequal 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.

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: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery. Cloud Knowledge: AWS/Azure/GCP Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert Proficient in Python, SQL, Javascript

Mandatory Skill sets

Gen AI,LLM,Huggingface,python,pytorch/tensor flow/keras,Langchain,Langgraph,Docker,Kunernetes

Preferred Skill sets

5-8 years

Years of Experience required

5 to 10

Education qualification

B.Tech/MCA/BCA/M.tech

Education

Degrees/Field of Study required: Bachelor of Technology

Required Skills

Project Management

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, AI Fluency, AI-Human Collaboration, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Coaching and Feedback, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity {+ 46 more}

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

September 20, 2026