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# ML Researcher

- **Company:** Air Apps
- **Location:** Barcelona, Spain
- **Salary:** €60,000.0 - €76,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Code Generation, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Software Engineering, Graphics Processing Unit (GPU), Large Language Models, Deep Learning, Kaggle, Information Technology, Machine Learning Operations
- **Published:** September 24, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## About the Role

+ Strong familiarity with the full research cycle in Machine Learning
 + Strong fundamentals of software engineering
 + Strong knowledge of Python, and its ML frameworks
 + Experience with:
o Full lifecycle of AI model development
o ML infrastructure frameworks and tools
o Developing new ML methods, algorithms and models
o GPUs (or TPUs) and distributed training
o Scaling up models and training regimes

 + Knowledge of:
o Classical ML methods and algorithms
o Deep Learning techniques, + Expertise within one of the following areas is a strong bonus: Architecture Research, Distillation (Model Compression), Evaluation, Code Generation, LLMs

 + Experience with foundational models, e.g. LLMs
 + Published research at AI conferences
 + Contributions to open source ML projects
 + Experience working with tabular data / predictive analytics
 + High Kaggle rank
 + BSc/MSc/PhD in computer science/machine learning

## Description

As part of the Research team, you will contribute to ideation, designing, implementing, and evaluating breakthrough Machine Learning models that will be deployed in the real world. Your work will be focused on the entire lifecycle of the models. Alongside the rest of the ML researchers in the team, you will be responsible for our models' performance in every meaning of this word - whether this means achieving high evaluation scores through novel architectures and training methods, establishing the evaluation protocols themselves, or implementing methods that allow for efficient training and inference. The greatest research is done through solid engineering, so alongside the research you will also take part in ensuring that our research code allows swift, rapid development and testing of new ideas - both your own and the rest of the team's.