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Tier-1 employer, metro location, senior title, but niche ML specialization reduces candidate pool.
Deep applied mathematics and advanced deep-learning expertise limit transferability across industries.
Explicit 10+ years, 5+ years specialized ML experience, and advanced degree requirements make filters very strict.
Own the end-to-end mathematical and statistical architecture of complex AI systems including data integration, model development, inference, and monitoring.
Design and implement scalable, robust, and secure deep learning and Agentic AI models for large-scale enterprise environments.
Provide technical mentorship and establish architectural standards, best practices for AI-centric systems across teams.
Masters or PhD in Computer Science, Applied Mathematics, Statistics, Physics, or a closely related quantitative discipline.
10+ years of software engineering experience with 5+ years in applied mathematics, statistical modeling, and deep learning systems.
Demonstrated experience architecting and deploying AI solutions in production environments.
Expert-level proficiency in Python and strong fundamentals in software engineering including data structures, algorithms, system design, and performance optimization.
Deep expertise in applied mathematics, statistical modeling, and advanced deep learning techniques with focus on transformers, state-space, and diffusion models.
Proven ability to translate complex business problems into formal mathematical models and deploy production-ready AI solutions at enterprise scale.
Experienced technical leader capable of influencing architectural decisions, mentoring teams, and driving adoption of best practices in AI model lifecycle management.