Hybrid Deep Learning Engineer for LLMs & AI

European Tech Recruit; Barcelona; Híbrido; EUR 45.000 - 70.000; Jornada completa

Descripción de la vacante

A fast-growing deep-tech company in Barcelona is seeking a motivated Deep Learning Engineer. The role involves designing and optimizing cutting-edge deep learning models, specifically in fields like quantum computing and AI. Candidates should have a Master’s or Ph.D. in a technical field and 3+ years of experience in deep learning, particularly in model compression and optimization. The position offers a hybrid working arrangement and the chance to work on challenging projects that shape future AI technologies.

Formación

• Master's or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, Physics, or a related field required.
• 3+ years of hands-on experience training deep learning models, including architectures and data pipelines.
• Proven experience in major deep learning domains like computer vision, speech recognition, or LLMs.
• Strong expertise in model compression, including pruning, distillation, and optimization techniques.

Responsabilidades

• Design, train, and optimize deep learning models from scratch.
• Develop and apply model compression techniques like pruning, distillation, and quantization.
• Integrate compressed models into production pipelines.
• Conduct empirical studies and deep error analysis.

Conocimientos

Deep Learning Model Training

Model Compression Techniques

Data Pipeline Development

Python

PyTorch

Performance Analysis

Communication Skills

Educación

Master’s or Ph.D. in Computer Science or related field

Herramientas

HuggingFace Transformers

DeepSpeed

Lightning

Descripción del empleo

A fast-growing deep-tech company in Barcelona is seeking a motivated Deep Learning Engineer. The role involves designing and optimizing cutting-edge deep learning models, specifically in fields like quantum computing and AI. Candidates should have a Master’s or Ph.D. in a technical field and 3+ years of experience in deep learning, particularly in model compression and optimization. The position offers a hybrid working arrangement and the chance to work on challenging projects that shape future AI technologies.