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Tier-1 brand, metro location, and broad high-demand ML/LLM requirements increase applicant competition.
Requires deep ML/LLM and production expertise, restricting easy transfer across non-ML industries.
Explicit 8+ years plus many mandatory ML/LLM, production, and causal ML requirements enforce strict filtering.
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Translate ambiguous business problems into well-defined analytical projects partnering directly with stakeholders.
Lead the development and deployment of end-to-end production ML/AI systems including classical ML, LLM/Generative AI, Agentic AI, causal inference, optimization, and recommendation.
Set and uphold technical standards through hands-on coding, mentorship, system design, and rigorous evaluation protocols.
8+ years in Applied ML/AI including experience with LLM and Generative AI, with at least 6 years hands-on production model deployment.
Bachelor's or higher in Computer Science, Statistics, Mathematics, Engineering, Economics or a related quantitative field, or equivalent demonstrable expertise.
Expert-level Python proficiency including scientific libraries (NumPy, pandas, scikit-learn, PyTorch) and experience with cloud platforms (AWS/Azure/GCP).
Deep knowledge of classical ML/statistics, NLP, causal ML, optimization, and practical experience with agentic AI frameworks (e.g., Langchain).
Hands-on technical leader comfortable balancing rigor, speed, and maintainability in production ML/AI systems.
Experienced in building robust, scalable data science and AI systems from scratch to deployment in complex business environments.
Skilled at navigating ambiguity to scope problems clearly and choosing the most effective ML/AI approach aligned with business impact.