Job highlights

- We are seeking an experienced Data Scientist (AI / ML) with over 8-12 years of experience specializing in Artificial Intelligence (AI) and Machine Learning (ML) to join our team
- MLOps Deployment: Utilization of containerization strategies for ML workloads,experience with model serving tools like TorchServe or TF Serving,and automated model retraining

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics AI

Management Level

Manager

Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes.

Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation.

About the Role

We are seeking an experienced Data Scientist (AI/ML) with over 8-12 years of experience specializing in Artificial Intelligence (AI) and Machine Learning (ML) to join our team. This is a hybrid work environment, providing flexibility and collaboration opportunities.



The successful candidate will play a pivotal role in shaping and leading AI/ML initiatives within our organization.

- Advanced proficiency in Python.
- Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques
- Experience with big data processing using Spark for large-scale data analytics
- Version control and experiment tracking using Git and MLflow
- Software Engineering Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.
- DevOps Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.
- LLM Infrastructure Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management.
- MLOps Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining.
- Cloud Infrastructure: Solid grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.

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.

📌 Manager_ AI/ML Engineer _ Data & Analytics (Bengaluru)
🏢 PwC Service Delivery Center
📍 Bengaluru