Description
Angible's models do not stay in notebooks. They have to watch live retail environments, process video continuously, and run reliably on hardware installed at physical stores.
That makes this Senior Machine Learning Engineer role as much about deployment engineering as model quality. Work can involve exporting PyTorch models through ONNX, optimizing FP16 or INT8 inference, tuning TensorRT and OpenVINO, managing video streams, and operating models across NVIDIA and Intel edge hardware.
Computer vision experience in detection, segmentation, tracking, or Re-ID is particularly useful. Familiarity with FFmpeg, RTSP, WebRTC, Docker, MLflow, ClearML, DVC, and production monitoring can also matter once models leave the training environment.
This is a strong fit for an ML engineer who enjoys the gap between “the model works” and “the system works every day in the real world.”
This opportunity was curated for Trainety from Angible's own career page. Verify current details with the company before applying.
https://www.angible.com/careers-senior-machine-learning-engineer-engineering