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Tier-1 brand, mid-level common title, and metro location increase applicant competition.
ML/LLM engineering skills are transferable but require domain-specific model and fine-tuning experience.
Explicit 5+ years and specific ML/LLM tech requirements make shortlisting highly selective.
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Design and develop common components, frameworks, and models to build AI native and Fullstack LLM applications.
Own end-to-end development of ML pipelines and frameworks tailored to use cases in collaboration with consuming teams.
Lead rapid prototyping and experimentation to create high accuracy and performant AI/ML solutions, adapting to shifts in GenAI/AI technology.
Bachelor's, Master's, or PhD in Computer Science or related field, or equivalent practical experience.
5+ years of experience building and designing AI/ML applications.
Proficiency in Python, PyTorch, TensorFlow, Numpy, and Pandas.
Experience with machine learning fundamentals and production-grade model development, plus knowledge of cloud integration (e.g., AWS Sagemaker).
Strong capability to navigate ambiguity and lead proof-of-concept initiatives with clarity.
Experience building and fine-tuning LLM applications using technologies like LangChain, CustomGPTs, and prompt management.
Skilled in setting and owning metrics for model accuracy and optimization, combining ML expertise with solid computer science fundamentals.