Machine Learning Engineer

About the Company

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 named by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.

With 180+ employees, our multicultural team delivers 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 industries by providing advanced compression for AI models and quantum‑inspired optimization platforms that deliver immediate performance gains on classical and quantum hardware.

Job Responsibilities

Design and develop techniques to compress Large Language Models (LLMs) using quantum‑inspired technologies for real‑world use cases.

Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement and fine‑tuning LLMs to enhance accuracy, robustness, and efficiency.

Build LLM‑based applications such as Retrieval‑Augmented Generation (RAG) systems and AI agents.

Assess strengths and weaknesses of models, proposing enhancements and novel solutions to improve performance and efficiency.

Act as a domain expert in LLMs, identifying opportunities for quantum‑AI driven innovation tailored to specific industry problems.

Maintain comprehensive documentation of development processes, experiments, and results.

Mentor junior team members, fostering a culture of learning and technical growth.

Participate in code reviews and provide constructive feedback to teammates.

Stay updated on the latest advancements in LLMs and recommend new tools and technologies as appropriate.

Required Qualifications

Bachelor’s, 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 Transformers.

Strong mathematical foundations and deep learning algorithm expertise for both training and inference.

Excellent problem‑solving, debugging, performance analysis, test design, and documentation skills.

Understanding of GPU architectures and LLM hardware / software infrastructures.

Proficient programming skills in Python with experience in PyTorch, HuggingFace and related libraries.

Experience with cloud platforms (ideally AWS), containerization technologies (Docker), and deploying AI solutions in a cloud environment.

Excellent written and verbal communication skills—effective collaboration in a fast‑paced team.

Previous research publications in deep learning or related tech fields are a plus.

Fluent in English.

Preferred Qualifications

Experience running large‑scale workloads on high‑performance computing clusters.

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

Experience handling large datasets and ensuring data quality.

Experience with inference and deployment environments such as TensorRT or vLLM.

Experience evaluating LLM accuracy using leaderboards like OpenLLM.

Experience building and evaluating RAG systems.

Familiarity with AI ethics and responsible AI practices.

Location & Benefits

Applicants must have legal authorization to work in the country where the position is based.

The role is hybrid with flexible working hours, private health insurance, equal pay guaranteed, and language classes.

We offer a high‑paced environment working on cutting‑edge technologies and a career plan for learning and teaching.

As an equal‑opportunity employer, Multiverse Computing is committed to building an inclusive workplace.

We welcome people from all backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions, ideologies, and sexual orientations.

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