Senior AI Architect - Visual Intelligence Specialist

beBeeComputerVision; Madrid; Presencial; EUR 50.000 - 80.000; Jornada completa

Descripción de la vacante

A technology company in Madrid is seeking a skilled Deep Learning Engineer specializing in Computer Vision. The role involves developing and deploying models for object detection, segmentation, and classification using advanced deep learning architectures. Candidates should have over 4 years of experience in the field, proficiency in Python and PyTorch, and the ability to optimize models for production environments.

Formación

• 4+ years of experience in deep learning applied to computer vision.
• Proficiency in Python and PyTorch.
• Solid understanding of CNNs and various computer vision techniques.
• Experience with Vision Transformers and Foundation Models.
• Familiarity with MLOps tools.

Responsabilidades

• Develop and deploy deep learning models for object detection, segmentation, and image classification.
• Leverage state-of-the-art architectures including Vision Transformers.
• Design and execute experiments to ensure reproducibility.
• Analyze model performance and optimize inference pipelines.

Conocimientos

Deep learning

Computer vision

Image analysis

Object detection

Segmentation

Classification

Software engineering

MLOps

PyTorch

Descripción del empleo

Deep Learning Engineer – Computer Vision

We are seeking a skilled Deep Learning Engineer – Computer Vision to tackle complex visual understanding tasks using state-of-the-art deep learning models.

This role is ideal for someone with a strong background in image analysis, object detection, segmentation, and classification who thrives in a collaborative environment.

The ideal candidate combines solid software engineering skills with expertise in modern computer vision techniques. Experience with PyTorch is essential, as is familiarity with advanced architectures such as Transformers, Foundation Models, and Vision-Language Models (VLMs). Hands-on experience deploying optimized models in on-premise high-performance environments is highly valued.

Key Responsibilities

• Develop and deploy deep learning models for object detection, segmentation, and image classification.
• Leverage state-of-the-art architectures including Vision Transformers, Foundation Models, and VLMs.
• Design and execute experiments, ensuring reproducibility and scientific rigor.
• Analyze model performance and iterate to achieve production-grade results.
• Optimize inference pipelines for efficiency and scalability.

Software Engineering & MLOps

Write clean, modular, and well-documented Python code.

Contribute to code reviews, pull requests, and team knowledge sharing.

Build and maintain training and deployment pipelines.

Integrate models into production systems using best practices.

Data & Infrastructure

Work with large-scale image datasets, including geospatial data.

Use GIS tools and libraries when needed.

Deploy and serve models on on-premise infrastructure using NVIDIA Triton for high-performance inference.

Qualifications

4+ years of experience in deep learning applied to computer vision.

Proficiency in Python and PyTorch.

Solid understanding of CNNs, object detection, segmentation, classification pipelines.

Experience working with Vision Transformers, Foundation Models, or multimodal architectures.

Familiarity with MLOps tools.