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Tier-1 employer, sought-after senior ML role with broad LLM/MLOps requirements and metro hybrid location.
Deep LLM, agentic AI, and MLOps expertise required makes cross-industry fit limited without ML specialization.
Explicit 7-10 years plus mandatory LLM, agentic AI, MLOps, and technical stack raises filtering rigor.
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Lead architectural design and deployment of AI/ML solutions addressing complex supply chain challenges with measurable business impact.
Drive methodology rigor in model development including predictive analytics, large language models (LLMs), agentic workflows, and AI system evaluation.
Collaborate cross-functionally to transition AI research into production, mentor teams on technical excellence, and ensure ethical AI practices and reproducibility.
Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or related quantitative field.
7-10 years professional experience in data science, analytics, or related discipline with expertise in statistical analysis.
Hands-on experience building and deploying LLM-powered applications and agentic AI systems in production.
Expert proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow), SQL; strong knowledge of advanced statistical and ML methods; experience with data engineering tools like Spark or Snowflake.
Experienced leader capable of translating high-level business objectives into scalable AI/ML architectures within supply chain or operational contexts.
Deep domain expertise in generative AI, LLMs, agentic AI frameworks, and associated production-level system design.
Strong strategic orientation toward experimental rigor, ethical AI deployment, and cross-functional execution in fast-paced environments.