Machine Learning Engineer (Service) (Fixed-term contract)

We are looking to fill this role immediately and are reviewing applications daily. Expect a fast transparent process with quick feedback.

Why join us

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 5080%.
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.

We offer

• Competitive annual salary starting from 55000 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.

Job Overview

We are seeking a skilled and experienced Machine Learning Engineer with a strong technical background in Generative AI to join our this role you will have the opportunity to leverage cutting-edge quantum and AI technologies to lead the design implementation and deployment in production environments of Generative AI systems 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 Generative AI and LLM technologies.

As a Machine Learning Engineer you will

• Build end-to-end Agentic AI systems and RAG pipelines that combine retrieval reasoning and planning capabilities integrating them into customer-facing solutions across cloud and edge environments.

• Design train and optimize deep learning models including Large and Small Language Models (LLMs and SMLs) applying fine-tuning strategies as core components that power our Agentic AI and RAG systems of client-facing solutions.

• Drive end-to-end ML system design encompassing data sourcing and curation training evaluation deployment monitoring and continuous iteration not just model development.

• Develop and refine rigorous evaluation frameworks that go beyond model benchmarks to assess system performance on task success key KPIs and user-level outcomes across diverse domains.

• Fine-tune and adapt language models using methods such as SFT prompt engineering and reinforcement or preference optimization tailoring them to domain-specific tasks and real-world constraints.

• Design and implement strategies for data curation and augmentation including pre-training and post-training data pipelines synthetic data generation and task-specific dataset creation tailored to downstream applications.

• Maintain high engineering standards including clear documentation reproducible experiments robust version control and well-structured ML pipelines.

• Contribute to team learning and mentorship guiding junior engineers and fostering best practices in ML system design training workflows evaluation and integration with production systems.

• Participate in code reviews offering thoughtful constructive feedback to maintain code quality readability and consistency.

• Stay up-to-date with emerging trends in ML and Generative AI and proactively recommend tools frameworks and methods to enhance our technology stack.

Required Minimum Qualifications

• Masters or Ph.D. in Computer Science Machine Learning Data Science Physics Engineering or related technical fields with relevant industry experience.

• 3 years of hands-on experience building training and deploying machine learning systems in production including at least 2 years focused on Generative AI RAG systems or Agentic AI.

• Proven experience designing training and fine-tuning deep learning models from scratch (e.g. LLMs computer vision transformer-based) including SFT prompt engineering and model alignment techniques.

• Proven experience with agent-based architectures (task decomposition tool use reasoning workflows) RAG architectures (retrievers vector databases rerankers) and orchestration frameworks (LangGraph LlamaIndex).

• Strong understanding of end-to-end ML system design including data sourcing and preparation training evaluation deployment monitoring and iteration.

• Experience with system-level evaluation and improvement including LLM-as-a-judge methods task-based success metrics user-focused KPIs human-in-the-loop validation and ablations/error analysis to identify and address failure modes.

• Solid experience with data curation and augmentation including pre-training and post-training pipelines and experience with synthetic data generation for downstream applications.

• Strong problem-solving and analytical skills with a system-thinking and customer-oriented mindset to translate complex business needs into technical solutions.

• Proficiency in Python and core ML/data libraries (e.g. PyTorch HuggingFace NumPy Pandas) with strong software engineering practices (Docker Git CI/CD reproducibility code reviews) and experience building robust modular and scalable ML codebases.

• Experience with cloud platforms (ideally AWS).

• Excellent communication skills with the ability to work collaboratively in a team environment document and explain design decisions experimental results and communicate complex ideas effectively.

• Fluent in English.

Preferred Qualifications

• Ph.D. in Machine Learning Computer Science or a related field with a focus on deep learning generative AI or agentic systems.
• Demonstrated experience building and deploying end-to-end Agentic AI or RAG systems in production environments (e.g. with LangGraph LangChain LlamaIndex or custom orchestration frameworks).
• Track record of open-source contributions technical publications or community engagement in the ML or generative AI ecosystem.
• Ability to work effectively in cross-functional teams collaborating with product customer and platform stakeholders to deliver practical high-impact AI solutions.

• Fluent in Spanish.

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.
Our flagship products address critical industry needs:

• CompactifAI a groundbreaking compression tool for foundational AI models reducing their size by up to 95% while maintaining accuracy enabling portability across devices from cloud to mobile and beyond.

• Singularity a quantum and quantum-inspired optimization platform used by blue-chip companies in finance energy and manufacturing to solve complex challenges with immediate performance gains.

Youll be working alongside world-leading experts in quantum computing and AI developing solutions that deliver real-world impact for global clients. We are committed to an inclusive ethics-driven culture that values sustainability diversity and collaboration a place where passionate people can grow and thrive. Come and join us!

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.