Description
Training a vision model is only one piece of an Edge AI product. Someone still has to make inference services, video pipelines, device deployments, versioning, rollback, logging, and recovery behave like a coherent software platform.
That production layer is where this Angible position sits.
The engineer will work primarily in Python and Linux environments around ML runtimes and video infrastructure, connecting models to APIs, edge services, cameras, containers, and deployment systems. Technologies mentioned around the role include FFmpeg, RTSP, GStreamer, DeepStream, ONNX, TensorRT, and OpenVINO.
A conventional backend engineer with strong production instincts can fit well if they have experience with model serving or high-throughput media systems. Likewise, an ML engineer who enjoys systems work may find the scope appealing.
Trainety has condensed the company's full listing into this overview. Use the original Angible page to verify the latest status.
https://www.angible.com/careers-senior-backend-engineer-ml-products-edge-ai