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Machine Learning Engineer (Fixed-term contract)

MULTIVERSE COMPUTING SL.

Barcelona

Híbrido

EUR 90.000 - 110.000

Jornada completa

Hace 2 días
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Descripción de la vacante

A European AI and quantum tech leader is seeking an experienced AI Engineer to design and develop cutting-edge models for language processing. You'll conduct evaluations, optimize model performance, and engage in collaborative projects. The ideal candidate has a strong background in deep learning, transformers, and programming. With a competitive salary starting from €45,000, along with unique bonuses and a hybrid work model, join a fast-growing innovative team transforming AI technology.

Servicios

Competitive annual salary
Signing bonus
Retention bonus
Relocation package
Flexible working hours

Formación

  • 2+ years of hands-on experience with designing, training, or fine-tuning deep-learning models.
  • Solid mathematical foundations and theoretical understanding of deep-learning algorithms.
  • Excellent problem-solving, debugging, and performance analysis skills.

Responsabilidades

  • Design and develop techniques to compress large language models.
  • Conduct rigorous evaluations and benchmarks of model performance.
  • Maintain comprehensive documentation of LLM development processes.

Conocimientos

Deep learning model design
Transformer models
Python programming
Cloud platforms (AWS)
HuggingFace libraries

Educación

Bachelor's, Master's, or Ph.D. in AI, Computer Science, or related fields

Herramientas

PyTorch
Docker
Descripción del empleo

We are a European deep-tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide – compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50‑80%. Joining us means working on cutting‑edge solutions that make AI faster, greener, and more accessible – and being part of a company often described as a "quantum‑AI unicorn in the making." About Multiverse Computing – Founded in 2019, we are a well‑funded, fast‑growing deep‑tech company with a team of 180+ employees worldwide. Recognized by CB Insights (2023 & 2025) as one of the Top 100 most promising AI companies globally, we are also the largest quantum software company in the EU. We are looking to fill this role immediately and are reviewing applications daily. Expect a fast, transparent process with quick feedback.

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Aufgaben

Design and develop new techniques to compress Large Language Models based on quantum‑inspired technologies to solve challenging use cases in various domains. Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement, and fine‑tune and optimize LLMs for enhanced accuracy, robustness, and efficiency. Build LLM‑based applications such as RAG and AI agents. Use your expertise to assess the strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency. Act as a domain expert in the field of LLMs, understanding domain‑specific problems and identifying opportunities for quantum‑AI‑driven innovation. Design, train, and deliver custom deep‑learning models for our clients. Work in diverse areas beyond LLM, e.g., computer vision. Maintain comprehensive documentation of LLM development processes, experiments, and results. Share your knowledge and expertise with the team to foster a culture of continuous learning, guiding junior members of the team in their technical growth and helping them develop their skills in LLM development. Participate in code reviews and provide constructive feedback to team members. Stay up to date with the latest advancements and emerging trends in LLMs and recommend new tools and technologies as appropriate.

Profil

Bachelor's, Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields. 2+ years of hands‑on experience with designing, training, or fine‑tuning deep‑learning models, preferably working with transformer or computer vision models. 2+ years of hands‑on experience using transformer models, with excellent command of libraries such as HuggingFace Transformers, Accelerate, Datasets, etc. Solid mathematical foundations and theoretical understanding of 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 and LLM hardware / software infrastructures. 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 or any tech field is a plus. Fluent in English.

Preferred Qualifications

Experience running large‑scale workloads in high‑performance computing (HPC) clusters. Experience in handling large datasets and ensuring data quality. Experience with inference and deployment environments (TensorRT, vLLM, etc.). Experience in accuracy evaluation of LLMs (OpenLLM Leaderboard). Experience building and evaluating RAG systems. Experience building non‑LLM deep‑learning applications, e.g., computer vision, audio, or signal processing. Familiarity with AI ethics and responsible AI practices. Experience in DevOps / MLOps practices in deep‑learning product development.

Wir bieten

Competitive annual salary starting from €45,000, based on experience and qualifications. Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion. Relocation package (if applicable). Fixed‑term contract ending in June 2026. Hybrid role and flexible working hours. Be part of a fast‑scaling Series B company at the forefront of deep tech. Equal pay guaranteed. International exposure in a multicultural, cutting‑edge environment.

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