Senior Machine Learning Engineer (LLM & GPU Architecture)

European Tech Recruit; Tarragona; Presencial; EUR 65.000 - 85.000; Jornada completa

Descripción de la vacante

A leading tech start-up in Spain is looking for a Senior Machine Learning Engineer to design and optimize Large Language Models using quantum technologies. The ideal candidate will have a Master’s or Ph.D. in AI or related fields, with over three years of experience in deep learning and strong proficiency in Python and GPU architecture. This role offers an exciting opportunity to innovate in quantum AI applications across multiple industries.

Formación

• 3+ years of hands-on experience with deep learning models.
• Proficiency in LLM and Transformer models using relevant libraries.
• Strong problem-solving and debugging skills.
• Solid understanding of GPU architectures.

Responsabilidades

• Design and develop techniques to compress Large Language Models.
• Conduct rigorous evaluations and benchmarks of model performance.
• Propose enhancements to improve performance and efficiency.
• Maintain comprehensive documentation of LLM development processes.

Conocimientos

Deep learning models

Large Language Models

GPU architecture

Python

Performance analysis

Collaboration

Educación

Master’s or Ph.D. in Artificial Intelligence, Computer Science, or related fields

Herramientas

PyTorch

HuggingFace Transformers

AWS

Docker

Descripción del empleo

Overview

Senior Machine Learning Engineer (LLM & GPU Architecture)

This is a great opportunity to work with one of the biggest growing tech start-ups based in Spain. They are well-funded and operate as a prominent quantum software company in Europe, delivering practical applications and value with their AI and LLM products across finance, energy, manufacturing, defence, cybersecurity, life sciences, and chemistry.

Responsibilities

• Design and develop new techniques to compress Large Language Models based on quantum-inspired technologies to solve challenging use cases across various domains.
• Conduct rigorous evaluations and benchmarks of model performance, identify areas for improvement, and fine-tune and optimise LLMs for accuracy, robustness, and efficiency.
• Assess strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency.
• Act as a domain expert in LLMs, understanding domain-specific problems and identifying opportunities for quantum AI-driven innovation.
• Maintain comprehensive documentation of LLM development processes, experiments, and results.
• Participate in code reviews and provide constructive feedback to team members.

Qualifications

• Master’s or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
• 3+ years of hands-on experience with deep learning models and neural networks, preferably with Large Language Models and Transformer architectures, or computer vision models.
• Hands-on experience using LLM and Transformer models, with proficiency in libraries such as HuggingFace Transformers, Accelerate, Datasets, etc.
• Solid mathematical foundations and expertise in deep learning algorithms and neural networks, both training and inference.
• Strong problem-solving, debugging, performance analysis, test design, and documentation skills.
• Strong understanding of GPU architectures and experience with Python and relevant libraries (PyTorch, HuggingFace, etc.).
• Experience with cloud platforms (ideally AWS), containerization (Docker), and deploying AI solutions in a cloud environment.
• Excellent written and verbal communication skills and ability to work collaboratively in a fast-paced team environment.
• Previous research publications in deep learning are a plus.

Keywords

Large Language Models / LLM / Machine Learning / AI / Quantum Computing / GPU Architecture / GPGPU / GPU Farms / Multi-GPU / AWS / Kubernetes Clusters / DeepSpeed / SLURM / RAY / Transformer Models / Fine-tuning / Mistral / Llama

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