Experience in manufacturing, industrial, or OT-adjacent domains (MES, SCADA, PLC integration, factory automation, IoT).
Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
Background with digital twins, predictive maintenance, OCR/IDP, computer vision, or speech-to-text model integrations.
Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton Inference Server).
Experience building RAG (Retrieval-Augmented Generation) systems, vector databases (Pinecone, Weaviate, Milvus), and LLM deployment pipelines.
Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows.
Experience in hyper-growth startup-like environments, with demonstrated success balancing speed, ambiguity, and long-term system health.
Familiarity with enterprise systems such as ERP, MES, WMS, PLM, or manufacturing planning systems.
Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.
Experience with MLOps tools including experiment tracking (MLflow, Weights & Biases), feature stores (Feast, Tecton), and model registries.
Experience in manufacturing industries with hands-on exposure to assembly lines or production environments.
Knowledge of edge ML deployment, model optimization (quantization, pruning), or deploying models on resource-constrained devices.
Eligible to obtain and maintain a U.S. Secret security clearance.
