AI/ML Engineer specialized in Computer Vision for Embedded Systems (Edge AI)
- Compensation
- Not disclosed
- Location
- GRANADA, Spain, Spain
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Nice to have
- The company will positively consider knowledge and experience in:
- Advanced object-detection architectures, recent YOLO variants, transfer learning, distillation, pruning, and quantisation-aware training.
- Qualcomm QCS/QCM, AI Hub, QNN SDK, Hexagon DSP/HTP acceleration, and on-target performance profiling.
- ONNX, TensorFlow Lite, OpenCV, model conversion, and heterogeneous CPU/GPU/DSP/NPU optimisation.
- MLOps: experiment tracking, dataset/model versioning, reproducible training, continuous integration, automated evaluation, and model release management.
- Synthetic data generation, active learning, hard-negative mining, domain adaptation, and techniques for limited or imbalanced datasets.
- Camera systems, image processing, infrared/multispectral imagery, video pipelines, calibration, tracking, or sensor fusion.
- Battery-powered edge products, defense, aerospace, optronics, wearables, or rugged, high-reliability applications.
- The keys of our offer:
- Be part of a leading and expanding company.
- Health insurance.
- Flexible work schedule.
- International and dynamic environment in Granada, Spain.
- High possibilities to grow inside the company.
- Professional Career Plan.
- Safran is an equal opportunity employer who does not discriminate based on race, color, citizenship, religion, gender, sexual orientation, national origin, age, disability or any protected category.
Full description
We're looking for an AI/ML Engineer specialized in Computer Vision for Embedded Systems (Edge AI) to join our Optronics team in Granada, Spain.
Our Technology:
Safran is a global leader in optronics, delivering advanced electro-optical systems for defense, aerospace, and security. Our portfolio features cutting-edge multispectral imaging technologies, including both infrared and visible-spectrum sensors integrated into airborne, naval, and land platforms for surveillance, reconnaissance, targeting, and navigation. Armed forces worldwide trust our solutions for their reliability, performance, and technological superiority.
We’re also a world leader in Resilient Positioning, Navigation and Timing (R-PNT), improving reliability, performance, and safety in critical applications and high-risk operations, even in GPS/GNSS-denied environments. We provide virtually fail-safe GNSS (Global Navigation Satellite Systems) and PNT (Positioning, Navigation and Timing) solutions for military and commercial applications worldwide.
Our industry-leading solutions combine ultra-accurate synchronization (sub-ns) and frequency distribution services. Built on enhanced White Rabbit PTP (Precision Time Protocol) synchronization technology, our products and technical solutions support a broad set of applications extending from timing distribution in financial networks to robust, reliable positioning.
We also specialize in control systems and diagnostics for particle accelerators and scientific facilities, providing innovative, dependable solutions with timing at their core.
The Position:
We are looking for an AI/ML Engineer specialized in Computer Vision for Embedded Systems (Edge AI) to develop vision for compact, battery-powered optronic products. The role covers data strategy, dataset generation, training, optimization, evaluation, deployment, and validation on Qualcomm QCS/QCM platforms.
Within the Optronics team, you will train and fine-tune classification and object-detection models, including YOLO, for efficient edge inference. You will quantize models with Qualcomm QNN, build deployment workflows using Qualcomm AI Hub, and integrate and validate models on embedded targets.
You combine strong computer vision and deep-learning expertise with practical embedded-systems knowledge. You use PyTorch and TensorFlow, design data-collection and annotation strategies, evaluate model quality and runtime performance, and collaborate with embedded software, hardware, systems, and product teams to deliver accurate, efficient, and maintainable AI capabilities for demanding field environments.
What you’ll be doing:
Define data-collection strategies reflecting product use cases, environments, sensor configurations, and target classes.