Machine Learning Engineer (Zaragoza y Barcelona) (temporal)

thexpeople; Valencia; Híbrido; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading technology firm in Valencia is looking for a Machine Learning Engineer to pioneer new techniques in AI using cutting-edge technologies. The role emphasizes design, development, and optimization of Large Language Models, requiring strong proficiency in deep learning and programming. Candidates should possess a relevant advanced degree and at least 2 years of applicable experience. The position offers a competitive salary, bonuses, and a flexible hybrid work model.

Servicios

Competitive annual salary

Signing and retention bonuses

Relocation package

Formación

• 2+ years of experience in designing, training or fine-tuning deep learning models.
• Solid understanding of deep learning algorithms and neural networks.
• Excellent programming skills in Python with relevant libraries.

Responsabilidades

• Design and develop new techniques for compressing Large Language Models.
• Conduct evaluations and benchmarks of model performance.
• Deliver custom deep learning models for clients.

Conocimientos

Deep learning model design

Problem-solving skills

GPU architectures knowledge

Experimental documentation

Collaboration in team environments

Mathematical foundations

TensorFlow/PyTorch

English fluency

Educación

Bachelor's, Master's or Ph.D. in AI, Computer Science or related

Herramientas

HuggingFace Transformers

Docker

AWS

Descripción del empleo

We Offer

• Competitive annual salary.
• 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.

As a 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‑tune and optimise 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.

Required Qualifications

• Bachelor's, Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
• 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 of the fundamentals of GPU architectures 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.

Preferred Qualifications

• 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.