SENIOR MACHINE LEARNING ENGINEER (LLM)

Multiverse Computing Multiverse is a well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. We are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international.We provide hyper-efficient software to companies seeking to gain an edge with quantum computing and artificial intelligence. Our main products, Singularity and CompactifAI, address critical needs across various industries. Singularity remains a trusted solution for blue-chip companies in finance, energy, manufacturing, cybersecurity, and more. CompactifAI, on the other hand, is a groundbreaking compression tool for foundational models based on Tensor Networks. With CompactifAi, one can compress AI systems, such as large language models, to make them more efficient and portable.You will be working alongside world leading experts to build solutions that tackle real life issues. We look for passionate people that want to grow in an ethics driven environment, promoting sustainability and diversity. We aim to continue building our truly inclusive culture - come and join us.

Job OverviewWe are seeking a skilled and experienced Machine Learning Engineer Senior and Mid level with a strong background in Large Language Models to join our team. In this role you will have the opportunity to leverage cutting-edge quantum and AI technologies to lead the design, implementation, and improvement of our language models, as well as working closely with cross-functional teams to integrate these models into our products. You will have the opportunity to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies. As a Senior Machine Learning Engineer, you will
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.

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.

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.
Required Qualifications
Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.














Mid: 2+ years of hands-on experience with deep learning models and neural networks, preferably working with Large Language models and Transformer
Senior: 5+ years of hands-on experience with deep learning models and neural networks, preferably working with Large Language models and Transformer architectures, or computer vision models
2+ year of 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 with the fundamentals 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 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 is a plus.
Fluent in English.
Preferred Qualifications
Proven experience (4+ years) delivering successful AI-driven projects in an industrial environment.
Spanish Language skills 

Experience running large-scale workloads in high-performance computing (HPC) clusters.

Experience in DevOps/MLOps practices in deep learning product development.

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.

Familiarity with AI ethics and responsible AI practices.
Perks and Benefits¡

Indefinite contract.
Equal pay guaranteed.
Variable performance bonus.
Signing bonus.
We offer work visa sponsorship (If applicable).
Relocation package (if applicable).
Private health insurance.
Eligibility for educational budget according to internal policy.
Hybrid opportunity.
Flexible working hours.
Language classes and discounted lunch options
Working in a high paced environment, working on cutting edge technologies.
Career plan. Opportunity to learn and teach.
Progressive Company. Happy people culture
As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.