Founding Product Engineer to build a greenfield physical AI product at Netradyne, working across full-stack infrastructure, product UX, and agentic AI features. You'll design multi-tenant cloud and edge systems on AWS with real-time dashboards, compliance analytics, and AI-powered agent orchestration for safety operations. Expected to own end-to-end problems—from device to cloud to customer—with 7+ years of software engineering across backend (Go, Python, Java), cloud infrastructure (containers, CI/CD, distributed systems), and modern frontend (TypeScript/JavaScript). Direct customer collaboration and rapid iteration in the field required; fluency with AI-assisted development tools (Claude, Cursor) expected.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams. The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.