Machine Learning Engineer (LLM)

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Machine Learning EngineerData

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Overview

Multiverse Computing Multiverse is a well-funded, fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.With 180+ employees and growing,…

Requirements Summary

Spanish Language skills Experience running large-scale workloads in high-performance computing (HPC) clusters. Experience in handling large datasets and ensuring data quality.

Technical Tools

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Multiverse is a well-funded, fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.
With 180+ employees and growing, our team is fully multicultural and international. We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.
Our flagship products, CompactifAI and Singularity, address critical needs across various industries:

CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systems—such as language models—to make them significantly more efficient and portable.
Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance, energy, manufacturing, and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.

You’ll be working alongside world-leading experts to develop solutions that tackle real-world challenges. We’re looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity.
We’re committed to building a truly inclusive culture—come and join us.

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-tuning and optimising 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.

Requirements

~1 min read

2+ years of hands-on experience with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models.

2+ year 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 with the fundamentals of GPU architectures and 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 with 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

Requirements

~1 min read

Spanish Language skills
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 in 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.