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Tier-1 brand, metro location, mid-level GenAI role increases applicant competition.
Technical GenAI and LLMOps skills are transferable, though advisory consulting experience moderately matters.
Explicit 3+ years and many mandatory GenAI/ML/LLMOps skills increase filtering.
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Design and manage ML pipelines including experiment, model, and feature management, and scalable model inferencing APIs.
Implement and optimize LLM serving architectures leveraging GPU and distributed training frameworks like DeepSpeed and vLLM.
Utilize DevOps and LLMOps tools including Kubernetes, Docker, and LLM orchestration frameworks to deploy and maintain AI models at scale.
Minimum 3+ years of experience in Generative AI, LLMs, and related ML pipeline design and deployment.
Proficient in Python, PyTorch/TensorFlow/Keras, Huggingface, Langchain, Langgraph, Docker, Kubernetes.
Bachelor’s degree in Engineering (BE/B.Tech) or equivalent (Master’s preferred but not mandatory).
Work Experience Required: 3+ years
Experienced in working with cloud AI platforms like AWS SageMaker, Azure AI, Vertex AI, and managing multi-cloud environments.
Strong hands-on knowledge of LLM fine-tuning, optimization, and orchestration frameworks suitable for large scale deployments.
Skilled in DevOps and container orchestration tools tailored for machine learning operations in advisory or consulting environments.