Applied Scientist - Computational Modeling, OMHS SCS
Core
Build self-optimizing fulfillment centers by developing production ML systems, physics-informed models, and embedded prototypes for material handling equipment (MHE) orchestration.
Role type
Senior Applied Scientist (Computational Modeling & Optimization)
Builds
Real-time building-wide orchestration of MHE, throughput optimization, and congestion control systems for Amazon fulfillment centers.
Domain
Logistics / Supply Chain / Robotics / Applied Mathematics
Deliverable
production ML models
Required skills
Applied mathematics, statistical modeling, machine learning, computer vision, optimization, first-principles modeling, Python, C++, Java, PyTorch, TensorFlow, NumPy, SciPy, scikit-learn, pandas
Preferred skills
PhD, physics-informed neural networks (PINNs), reinforcement learning, signal processing, controls, physical modeling, hardware prototyping, edge compute optimization, peer-reviewed publications
Technologies
PyTorch, TensorFlow, NumPy, SciPy, scikit-learn, pandas, C++, Java
Responsibilities
Frame ambiguous business problems as tractable scientific problems, prototype end-to-end solutions for sensing hardware and edge-deployable models, integrate solutions into deployment architecture, optimize models for resource-constrained hardware
Seniority
Senior, hands-on IC