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 one of the most well-known quantum software companies in Europe. They provide hyper-efficient software to companies seeking to gain an edge with quantum computing and artificial intelligence across finance, energy, manufacturing, defence, cybersecurity, life sciences, and chemistry, delivering practical applications and tangible value with their new AI & LLM product.
Responsibilities
* Design and implement 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 improvement areas, 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.
Required 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 excellent command of libraries such as HuggingFace Transformers, Accelerate, Datasets, etc.
* Solid mathematical foundations and expertise in deep learning algorithms and neural networks, both training and inference.
* Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.
* Strong understanding of GPU architectures.
* Excellent programming skills in Python and experience with relevant libraries (PyTorch, HuggingFace, etc.).
* Experience with cloud platforms (ideally AWS), containerization technologies (Docker) and deploying AI solutions in a cloud environment.
* Excellent written and verbal communication skills, with the ability to work collaboratively in a fast-paced team environment and communicate complex ideas effectively.
* Previous research publications in deep learning is a plus.
Key Words
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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