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PwC brand, Bangalore metro location, and mid-level ML role increase candidate competition.
Specialized GenAI, LLM, and PyTorch expertise reduce cross-industry transferability.
Explicit 4–7 years plus mandatory LLM, PyTorch, cloud, and CI/CD requirements make shortlisting highly strict.
Design, build, and deploy scalable Generative AI solutions using state-of-the-art LLMs and transformer architectures.
Fine-tune foundation models using domain-specific datasets and implement model pipelines with Python, PyTorch, and Hugging Face Transformers.
Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP) ensuring scalability, robustness, and compliance.
4 to 7 years of relevant work experience.
Bachelor’s degree required (B.E/B.Tech/M.Tech/MCA).
Mandatory skills: Generative AI (LLMs, Transformers), Python, PyTorch, Hugging Face Transformers, cloud platform experience (Azure/AWS/GCP), LangChain or similar orchestration frameworks, REST APIs (FastAPI/Flask), ML pipelines (MLflow, Weights & Biases), Git, CI/CD for ML (Azure ML/SageMaker).
Preferred experience with test automation; no explicit mention of notice period or specific location constraints.
Experienced in developing and deploying complex AI/ML solutions on cloud infrastructure with strong orchestration and pipeline automation skills.
Proficient at integrating GenAI models into enterprise applications via APIs, with ability to fine-tune and optimize large language models for domain-specific use cases.
Comfortable working at the intersection of AI research and enterprise deployment, collaborating cross-functionally with data engineering and MLOps teams in a fast-paced advisory environment.