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Metro location and broad LLM/MLOps skillset increase applicant competition.
Highly specialized ML/LLM and MLOps requirements limit cross-industry transferability.
Explicit 10+ years, leadership requirement, and detailed mandatory ML/LLM and MLOps skills indicate high strictness.
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Lead design, architecture, and implementation of large-scale machine learning programs across multiple projects, owning technical vision and roadmap.
Define success metrics, drive a metrics-driven culture, and communicate business impact of ML initiatives with clear linkage to outcomes.
Mentor junior data scientists/ML engineers, conduct reviews, and manage cross-functional stakeholder communications including senior leadership.
PhD or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related field (or equivalent practical experience).
10+ years of hands-on experience in machine learning or related fields; 4+ years leading technical projects/programs.
Expert-level proficiency with machine learning frameworks (TensorFlow, PyTorch) and strong software engineering skills in Python with production-grade code experience.
Experience deploying ML models/LLM agents to production at scale; proficiency with ML infrastructure, cloud platforms (AWS, GCP, Azure), and containerization (Docker, Kubernetes).
Experienced technical leader with proven ability to own and execute complex, multi-project ML programs involving ambiguous problems.
Strong specialized expertise in LLMs, multi-agent systems, instruction tuning, and ML observability aligned to enterprise-scale deployments.
Demonstrated skill in stakeholder management and communication with senior leadership, translating complex technical concepts into business impact.