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Tier-1 employer with mid-level ML role and publication requirements increases applicant competition moderately.
Core ML skills transferable, but logistics optimization specialization increases domain specificity.
Requires PhD or Master's+4, publications, and production ML experience, creating strict screening.
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Lead and grow a team of Applied Scientists, providing mentorship and technical guidance.
Own scientific vision and roadmap for ML solutions in large-scale transportation planning and execution.
Deliver production-ready, scalable ML models influencing customer experience, cost optimization, and network reliability.
3+ years building models for business applications.
PhD or Master's with 4+ years experience in CS, CE, ML or related fields.
Experience programming in Java, C++, Python or related languages.
Experience in algorithms, data structures, numerical optimization, or high-performance computing.
Experienced in leading ML model design across tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning.
Ability to guide technical design, experimentation, and drive roadmap execution balancing near-term delivery with long-term innovation.
Strong partnership skills with Product, Operations, and Engineering leaders to ensure scalable and robust solutions.