Lead Applied Scientist, Supply Chain Foundational Modeling

1) Lead Applied Scientist responsible for developing a novel foundational model for complex tabular data within a fast-paced, startup-like environment. 2) Design, implement, and deploy AI models addressing global supply chain and manufacturing challenges, and build production-ready ML pipelines with monitoring and telemetry. 3) Stay at the forefront of AI, applying and extending state-of-the-art techniques while inspiring cross-team AI initiatives. 4) Collaborate with Engineering, Design, Product Management, and domain experts to deliver scalable features used by major enterprises worldwide. 5) Establish robust evaluation frameworks with domain benchmarks and automated tests, and monitor model performance, data drift, and system health in production. 6) Candidates should have a Masters or PhD in Computer Science or a quantitative field with 5-7+ years of experience, deep learning and graph theory expertise, distributed training (DDP/FSDP, DeepSpeed, TorchTitan), Python and ML tooling (Kubeflow, Airflow, MLflow) and strong end-to-end MLOps skills.