Padmi

IN_Senior Associate GEN AI Engineer_ Emerging Technologies (Bengaluru)

BangalorePosted 1 month ago
Software engineeringSeniorFull Time; Regular
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Line of Service Advisory Industry/Sector Not Applicable Specialism Operations Management Level Senior Associate Job Description & Summary At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver creative software products and solutions. In emerging technology at PwC, you will focus on exploring and implementing cutting-edge technologies to drive innovation and transformation for clients. You will work in areas such as artificial intelligence, blockchain, and the internet of things (IoT). We are seeking a highly skilled and innovative GenAI Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and deploying scalable Generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures. This includes building intelligent applications, orchestrating model workflows, and integrating GenAI capabilities into enterprise systems. This role demands deep expertise in Python, PyTorch, and Hugging Face Transformers, along with hands-on experience in deploying solutions on Azure, AWS, or GCP. The candidate should be proficient in using orchestration frameworks like LangChain, developing APIs with FastAPI or Flask, and managing ML pipelines using tools such as MLflow or Weights & Biases. Familiarity with CI/CD practices for ML, including platforms like Azure ML or SageMaker Pipelines, is essential. Responsibilities: - Design, build, and deploy generative AI solutions using LLMs such as OpenAI, Anthropic, Mistral, or open-source models (e.g., LLaMA, Falcon). - Fine-tune and customize foundation models using domain-specific datasets and techniques. - Develop and optimize prompt engineering strategies to drive accurate and context-aware model responses. - Implement model pipelines using Python .

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