Embedded Vision AI Engineer (Edge, Qualcomm)

Safran; Granada; Vor Ort; EUR 55.000 - 75.000; Vollzeit

Benefits dieser Stelle

Health insurance

Flexible work schedule

International environment in Granada,

Zusammenfassung

Safran in Granada, Spain, seeks an AI/ML Engineer specialized in Computer Vision for Embedded Systems (Edge AI) to develop compact, battery-powered optronic vision solutions. You will handle data strategy, dataset generation, training, optimization, evaluation, deployment, and validation on Qualcomm QCS/QCM platforms.

You will train and fine-tune object-detection models including YOLO, quantize with Qualcomm QNN, and build deployment pipelines using Qualcomm AI Hub, delivering robust edge

Qualifikationen

• Bachelor’s or Master’s degree in Computer Science, AI, Telecommunications, Electronics, Software Engineering, or equivalent.
• At least three years’ professional experience developing computer-vision, machine-learning, or deep-learning solutions.
• Hands-on PyTorch and/or TensorFlow experience in development, training, fine-tuning, and experimentation.
• Experience training and fine-tuning image-classification and object-detection models, including YOLO architectures.
• Dataset expertise: collection, annotation, augmentation, balancing, versioning, quality control, and train/validation/test splits.
• Experience evaluating accuracy and robustness with suitable metrics, analysing errors, and improving models/datasets.
• Experience optimising and quantising networks for edge deployment, including Qualcomm QNN.
• Experience with Qualcomm AI Hub or equivalent conversion, compilation, profiling, and deployment toolchains.
• Embedded Linux knowledge; practical AI deployment/debugging on Qualcomm QCS/QCM or comparable ARM-based edge platforms.
• Proficiency in Python, Git, Linux, systematic debugging; strong analytical, communication, and professional English skills.

Aufgaben

• Define data-collection strategies reflecting product use cases, environments, sensor configurations, and target classes.
• Generate, curate, annotate, version, and quality-check image/video datasets for classification and object detection.
• Train and fine-tune classification and detection models with PyTorch and TensorFlow, including YOLO detectors.
• Design training/validation experiments, tune hyperparameters, analyse failures, and improve generalisation.
• Evaluate accuracy, precision, recall, F1, mAP, latency, memory, power, and robustness.
• Optimise and quantise networks with Qualcomm QNN, balancing quality, compute, memory, latency, and power.
• Build and maintain Qualcomm AI Hub pipelines: conversion, compilation, profiling, validation, and release packaging.
• Deploy and integrate models on Qualcomm QCS/QCM; troubleshoot preprocessing, inference, post-processing, and application interfaces.
• Validate end-to-end vision performance on representative hardware, cameras, datasets, and operational scenarios.
• Collaborate with embedded software, hardware, systems, verification, cybersecurity, and product teams; document reproducible workflows and test evidence.

Kenntnisse

Computer Vision

Deep Learning

PyTorch

TensorFlow

Edge AI

Qualcomm QNN

Ausbildung

Bachelor’s or Master’s degree

Tools

Qualcomm AI Hub

QNN SDK

Hexagon DSP/HTP

OpenCV

ONNX

Jobbeschreibung

Safran in Granada, Spain, seeks an AI/ML Engineer specialized in Computer Vision for Embedded Systems (Edge AI) to develop compact, battery-powered optronic vision solutions. You will handle data strategy, dataset generation, training, optimization, evaluation, deployment, and validation on Qualcomm QCS/QCM platforms.

You will train and fine-tune object-detection models including YOLO, quantize with Qualcomm QNN, and build deployment pipelines using Qualcomm AI Hub, delivering robust edge