Machine Learning Engineer (Service) (Fixed term contract)

Job description

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 breakthrough technology compresses large language models by up to 95% while maintaining accuracy and cuts 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.”

Benefits

• Competitive annual salary starting from €55,000, 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.
  
  

Job Overview

We are seeking a skilled and experienced Machine Learning Engineer with a strong technical background in Generative AI to join our team.

In this role you will design, implement, and deploy in production Generative AI systems, and work closely with cross‑functional teams to integrate these models into our products.

Responsibilities

• 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 LLMs and SMLs, applying fine‑tuning strategies that power our Agentic AI and RAG systems.
  
  
• Drive end‑to‑end ML system design, encompassing data sourcing, training, evaluation, deployment, monitoring, and continuous iteration.
  
  
• Develop and refine rigorous evaluation frameworks that assess system performance on task success, key KPIs, and user‑level outcomes across diverse domains.
  
  
• Fine‑tune and adapt language models using 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 and synthetic data generation.
  
  
• Maintain high engineering standards, with 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.
  
  
• Participate in code reviews, offering thoughtful, constructive feedback to maintain code quality and consistency.
  
  
• Stay up‑to‑date with emerging trends in ML and Generative AI, recommending tools, frameworks, and methods to enhance our technology stack.
  
  

Required Minimum Qualifications

• Master's 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, including SFT, prompt engineering, and alignment techniques.
  
  
• Proven experience with agent‑based architectures, RAG architectures, and orchestration frameworks such as LangGraph or LlamaIndex.
  
  
• Strong understanding of end‑to‑end ML system design, including data sourcing, training, evaluation, deployment, monitoring, and iteration.
  
  
• Experience with system‑level evaluation and improvement, including LLM‑as‑a‑judge methods, user‑focused KPIs, and ablation analysis.
  
  
• Solid experience with data curation and augmentation, including pre‑training and post‑training pipelines and synthetic data generation.
  
  
• Strong problem‑solving and analytical skills, with a system‑thinking and customer‑oriented mindset.
  
  
• Proficiency in Python and core ML/data libraries (PyTorch, HuggingFace, NumPy, Pandas), with strong software engineering practices and experience building scalable ML codebases.
  
  
• Experience with cloud platforms (ideally AWS).
  
  
• Excellent communication skills, with the ability to work collaboratively in a team environment.
  
  
• 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.
  
  
• 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.
  
  
• Fluent in Spanish.
  
  

About Multiverse Computing

Founded in 2019, Multiverse Computing is 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 include:

• CompactifAI – a compression tool that reduces foundational AI models by up to 95%, enabling portability across devices.
  
  
• Singularity – a quantum‑and‑quantum‑inspired optimization platform used by blue‑chip companies to unlock performance gains.
  
  

We provide solutions that deliver real‑world impact for global clients and are committed to an inclusive, ethics‑driven culture that values sustainability, diversity, and collaboration.

Equal Opportunity Statement

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.

Required Skill Profession

Ingeniería Y Tecnología