We are looking for a Machine Learning Engineer with strong practical experience in computer vision and neural networks to join our team.
The successful candidate will work on the research, development, training, optimization, and deployment of machine learning systems for current and future FluxPose hardware products. This is a hands-on technical role covering the full development cycle, from experimentation and dataset creation to deployment on production hardware.
We are looking for someone capable of independently solving technically uncertain problems and turning research or prototypes into reliable real-time systems.

Responsibilities

• Design, train, evaluate, and improve machine learning models for real-time sensing and tracking applications.
• Develop computer vision and image-processing systems.
• Build and maintain datasets, data collection pipelines, and evaluation tools.
• Generate synthetic training data where appropriate.
• Optimize models for accuracy, latency, memory usage, and computational cost.




• Quantize and deploy neural networks to embedded or hardware-accelerated platforms.
• Develop tools for training, visualization, benchmarking, and automated evaluation.
• Investigate real-world failure cases and improve model robustness.
• Collaborate closely with embedded, electronics, mechanical, and software engineers.

Mandatory Requirements

• Strong practical knowledge of machine learning and neural networks.
• Strong Python skills.
• Experience with PyTorch or a similar modern ML framework.
• Good understanding of computer vision and image processing.
• Experience training, evaluating, and debugging neural networks.
• Good understanding of datasets, augmentation, validation, overfitting, and model generalization.
• Ability to work independently and take ownership of complex technical problems.
• Strong problem-solving skills and attention to detail.
• Fluent English.

Major Advantages

Experience with Edge AI, TinyML, or embedded neural-network dep

📌 Machine Learning Engineer (España)
🏢 FluxPose
📍 España