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IN_Senior Associate_Gen AI_Emerging Businesses_Advisory_Bangalore

PwC
Karnataka, IND
Full-time
Onsite
Discovered 1 weeks ago
Generative AILarge language modelsTransformer architecturesPythonPyTorchHugging Face Transformers
Free

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Generative AILarge language modelsTransformer architectures
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Role Overview

PwC is seeking a Senior Associate GenAI Engineer for its Emerging Technologies advisory practice.

The role focuses on designing, developing, and deploying scalable generative AI solutions using LLMs and transformer architectures.

Responsibilities

  • Design, build, and deploy generative AI solutions using OpenAI, Anthropic, Mistral, LLaMA, Falcon, or other models.
  • Fine-tune foundation models with domain-specific datasets and techniques.
  • Develop prompt engineering strategies for accurate and context-aware model responses.
  • Build model pipelines with Python, PyTorch, Hugging Face Transformers, or LangChain.
  • Implement agentic AI solutions using CrewAI, LangChain, or related frameworks.
  • Productionize GenAI models with data engineering and MLOps teams on cloud platforms.
  • Use Azure AI Foundry, Google Cloud Vertex AI, or similar cloud AI platforms.
  • Ensure deployed models are robust, scalable, and compliant.
  • Integrate GenAI into enterprise applications through APIs or custom interfaces.
  • Evaluate model performance and improve outputs through iterative experimentation.
  • Track current research in GenAI, foundation models, and open-source tools.

Mandatory Skills

  • Generative AI, LLMs, and transformer architectures are required.
  • Python, PyTorch, and Hugging Face Transformers are required.
  • Azure, AWS, or GCP cloud experience is required.
  • LangChain, LangGraph, or similar orchestration framework experience is required.
  • REST API development with FastAPI, Flask, or similar tools is required.
  • ML pipeline experience with MLflow or Weights & Biases is required.
  • Git and CI/CD for ML, including Azure ML or SageMaker Pipelines, are required.

Preferred Skills

  • RAG and vector databases such as FAISS, Pinecone, or Weaviate are preferred.
  • Streamlit or Gradio, Docker or Kubernetes, and data preprocessing or feature engineering are preferred.
  • Experience with spaCy, NLTK, or related NLP libraries is preferred.
  • Fine-tuning models and working with small language models are advantageous.

Experience and Education

  • Four to seven years of experience is required.
  • The posting lists B.E., B.Tech, M.Tech, or MCA as education qualifications and separately identifies Bachelor of Technology as required.

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