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Strong Tier‑1 brand and metro location increase competition, but senior ML specialization narrows the candidate pool.
Specialized ML/LLM expertise and production experience limit cross-industry transferability.
Explicit 8+ years, lead experience, and mandatory ML/LLM tech stack create strict shortlisting.
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Design and own development of AI native app components, frameworks, and ML pipelines to enable different business use cases.
Lead rapid prototyping, experimentation, and iterations to deliver high accuracy and performant AI frameworks/models in collaboration with AI scientists and cross-functional teams.
Continuously explore advancements in GenAI/AI and integrate applicable innovations into existing applications to improve performance.
8+ years experience in building/designing AI/ML applications with at least 1 year in a leading role managing AI/ML engineers.
BS, MS, or PhD in Computer Science or related field, or equivalent practical experience.
Strong proficiency in Python, PyTorch, TensorFlow, Numpy, Pandas, and machine learning fundamentals including supervised, unsupervised, and reinforcement learning.
Experience with integrating AI/ML applications on cloud platforms such as AWS Sagemaker, and knowledge of LLM technologies including LangChain, CustomGPTs, and prompt management.
Demonstrated ability to lead AI/ML engineering teams and deliver end-to-end machine learning solutions in production environments.
Deep understanding of ML principles and metrics ownership focused on optimizing accuracy and performance.
Experience navigating ambiguity and driving clarity in complex AI product development with a focus on generative AI and large language models.