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Tier-1 brand, metro location, and mid-level (3+ yrs) role increase candidate competition.
Highly specialized GenAI and LLMOps skills limit cross-industry transferability.
Mandatory GenAI/LLM, MLOps, and specific tooling create strict shortlisting filters.
Design and manage machine learning pipelines including experiment, model, and feature management plus model retraining.
Develop scalable APIs for model inferencing and optimize large language models (LLMs) through fine-tuning and resource reduction.
Implement and maintain DevOps practices and LLMOps including container orchestration (Kubernetes, Docker) and LLM orchestration frameworks (Flowise, Langflow, Langgraph).
Minimum 3+ years of relevant experience in Generative AI and data analytics roles.
Mandatory skills: Generative AI, Large Language Models (LLM), Python, PyTorch/TensorFlow/Keras, Hugging Face, Langchain, Langgraph, Docker, Kubernetes.
Education: Bachelor or Master of Engineering, B.Tech, MBA, or MCA degree required.
Work Experience Required: 3+ years
Expertise in advanced ML model management and deployment, especially for large language models in cloud environments including AWS, Azure, or GCP.
Hands-on experience with MLflow, SageMaker, Vertex AI, and distributed training frameworks such as DeepSpeed and vLLM.
Strong practical skills in DevOps/LLMOps with Kubernetes, Docker, and experience working with modern LLM orchestration tools.