This role focuses on leveraging advanced analytics techniques to extract insights from large datasets and drive data-driven decision-making for clients
Job Summary
This role focuses on leveraging advanced analytics techniques to extract insights from large datasets and drive data-driven decision-making for clients.
You will be part of a vibrant community of solvers at PwC that leads with trust and creates distinctive outcomes through purpose-led work.
The position requires designing scalable ML pipelines and APIs while optimizing large language models for better latency and accuracy.
Matching Summary
This role focuses on leveraging advanced analytics techniques to extract insights from large datasets and drive data-driven decision-making for clients.
Skills & Requirements
Must-have
Gen AI and Large Language Models expertise
Python programming with PyTorch or TensorFlow
ML pipeline design using MLflow and SageMaker
LLM orchestration frameworks like Langchain and Langgraph
Docker and Kubernetes container orchestration
GPU architecture knowledge for distributed training
Cloud platform proficiency in AWS, Azure, or GCP
Nice-to-have
Experience with OLTP and OLAP environments
Knowledge of Kafka and Hadoop big data tools
Azure DevOps CI/CD integration experience
Understanding of Agile delivery methodologies
Familiarity with Flowise and Langflow tools
Proficiency in Javascript alongside Python
Experience with DeepSpeed for model parallelism
Key Requirements
5-8 years of professional experience required
Bachelor of Engineering, MCA, BCA, or Master's degree