qubitsok.com
Cut Noise. Work Quantum.
Europe, Spain, Madrid
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Posted 136 days ago
🏢 Multiverse Computing
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EUR 45K - 45K per year
Role Type
Role Focus
Seniority
Employer Type
This role is for a Machine Learning Engineer to develop new methods for compressing large language models using quantum-inspired technologies. The engineer will evaluate and fine-tune these models to improve their performance and efficiency. They will also build applications based on large language models, contributing to making AI more accessible and sustainable.
Key Responsibilities
Design and develop new techniques to compress Large Language Models using quantum-inspired technologies.
Evaluate and optimize large language models for better accuracy, robustness, and efficiency.
Build applications using large language models, such as Retrieval Augmented Generation (RAG) and AI agents.
Design, train, and deliver custom deep learning models for clients.
Maintain thorough documentation of development processes and share knowledge to support team growth.
Required Skills
2+ years of hands-on experience with designing, training, or fine-tuning deep learning models.
2+ years of hands-on experience using transformer models and libraries like HuggingFace Transformers.
Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks.
Excellent programming skills in Python with libraries such as PyTorch and HuggingFace.
Strong understanding of GPU architectures and LLM hardware/software infrastructures.
Experience with cloud platforms (AWS), containerization (Docker), and deploying AI solutions in a cloud environment.
Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.
Nice-to-have Skills
Experience running large-scale workloads in high-performance computing (HPC) clusters.
Experience with inference and deployment environments such as TensorRT or vLLM.
Experience building and evaluating RAG (Retrieval Augmented Generation) systems.
Experience in building non-LLM deep learning applications like computer vision or audio processing.
Familiarity with AI ethics and responsible AI practices.
Experience in DevOps/MLOps practices for deep learning product development.
Previous research publications in deep learning or any tech field.
Technology Tags
The core responsibility of the role involves designing, developing, and optimizing machine learning approaches, specifically for LLMs and deep learning.
The role is for a Machine Learning Engineer working for a "quantum and AI" leader, developing LLM compression using "quantum-inspired technologies," directly aligning with Quantum ML.
The role involves optimizing Large Language Models for enhanced accuracy, robustness, and efficiency.
The job focuses on developing techniques for LLM compression based on "quantum-inspired technologies," implying work with hybrid (classical-quantum inspired) algorithms.
The job requires excellent programming skills in Python for developing and maintaining AI solutions.
The job explicitly requires experience with cloud platforms, ideally AWS, for deploying AI solutions.
The role requires understanding LLM hardware/software infrastructures and experience with cloud platforms, containerization, and HPC clusters.