- Own customer-facing technical deployments from zero-to-one build through adoption, production launch, and post-deployment maintenance.
- Embed on-site with customers approximately 40% to 50% of the time to move validated proofs of concept into production.
- Build and configure data pipelines, edge devices, computer vision models, and supporting infrastructure.
- Write production-grade Python and solve issues involving lighting variability, camera calibration, model drift, networking, and edge-hardware constraints.
- Work across Docker, Kubernetes, Linux, NVIDIA Jetson, industrial cameras, computer vision, MLOps, and edge-computing systems.
- Build trust with customer executives, engineers, and floor operators.
- Surface field insights to Product and Engineering and improve the core platform.
- Document deployment architectures, create runbooks, and hand successful customers to implementation teams.
DockerPythonIoT+5 more