Sr Associate_Gen AI_Data and Analytics_Advisory

Job 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.

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: Proficiency in DevOps and LLMOps practices.
• Proven expertise in DevOps and LLMOps practices.
• Kubernetes, Docker, and container orchestration knowledge.
• Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph.
• 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, Spanner, BigQuery

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