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High: strong PwC brand, Bengaluru metro role, and mid-level 3+ years amplifies candidate competition.
High because specialized GenAI, LLM, and MLOps expertise limits cross-industry transferability.
High due to explicit 3+ years and mandatory GenAI, LLM, PyTorch, Kubernetes, and MLOps skill requirements.
Design and manage machine learning pipelines including experiment, model, and feature management, along with scalable model inferencing APIs.
Develop and optimize large language models (LLMs) leveraging GPU architectures and distributed training frameworks to improve latency and accuracy.
Implement DevOps and LLMOps practices using Kubernetes, Docker, and orchestration frameworks to support model deployment and operationalization.
Minimum 3+ years of relevant experience in generative AI, LLM development, and data analytics.
Mandatory skills: Generative AI, LLM, Huggingface, Python, PyTorch/TensorFlow/Keras, Langchain, Langgraph, Docker, Kubernetes.
Educational qualification: Bachelor or Master of Engineering (BE/B.Tech or ME) or equivalent (MBA/MCA mentioned but primary is engineering degree).
Work Experience Required: 3+ years explicit; Notice period: Not explicitly mentioned.
Experienced in advanced machine learning pipeline design and large-scale LLM training and deployment in cloud environments (AWS/Azure/GCP).
Strong technical expertise in GPU-based distributed model training and fine-tuning with frameworks like DeepSpeed and vLLM.
Capable of implementing robust MLOps/DevOps workflows using container orchestration and orchestration frameworks for LLMs, emphasizing operational efficiency and scalability.