Senior/ Lead - AI Research Engineer – Agents Team - MAD/BCN/ MUN

Aily Labs; Barcelona; On-site; EUR 90,000 - 120,000; Full time

Job summary

Aily Labs in Barcelona is seeking a Senior/Lead AI Research Engineer for the Agents Team to push frontiers in LLMs, Agentic AI, and advanced ML systems. You will design experiments, fine-tune models, and build reproducible research pipelines that scale in production.

You’ll work with a small, highly technical team, reporting on experiments, sharing insights, and collaborating to deliver tangible product enhancements while pursuing top-tier conference publications when possible.

Qualifications

• Exceptional AI researchers with strong ML background.
• Deep understanding of LLMs and agentic AI concepts.
• Ability to design, run, and reproduce experiments.

Responsibilities

• Design, set up, and execute experiments focusing on LLMs and agentic AI.
• Manage reproducible research pipelines, version code and data.
• Fine-tune state-of-the-art models and translate results into product improvements.
• Explain AI findings clearly and align experiments with team goals.
• Maintain high-quality, modular code following software engineering best practices.

Skills

LLMs

Agentic AI

Machine Learning

Experiment Design

Model Fine-Tuning

Code Quality

Tools

PyTorch

TensorFlow

Job description

Senior/ Lead - AI Research Engineer – Agents Team - MAD/BCN/ MUN

Full-time

Mission

Are you ready to take part in the upcoming AI revolution of the business world? If the answer is a resounding "yes," we have an extraordinary opportunity for you!

About Us

Aily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models and agentic AI to give business leaders clear, actionable insights in real time.

Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations powered by GenAI that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.

Founded in 2020 in Munich, Aily Labs has grown into a global team of 350+ people across Munich, Barcelona, Madrid, Cluj, and New York. Our mission is to democratize AI in business and enable leaders to Lead Boldly, turning complex data into decisions that drive real, measurable impact.

About the Team & The Role:

We are looking for exceptionally smart and driven AI Research Engineers to join a small, highly technical, and specialized research team at Aily.

This team operates at the bleeding edge of AI, focusing on high-impact, moderately higher-risk projects that directly influence our end product. While your day-to-day work will heavily involve Language Models and Agentic AI, we expect you to be deeply versed in all of Machine Learning. You will have the runway to dive deep into model architectures, debug complex algorithmic behaviors, fine-tune state-of-the-art models, and translate your findings into deployable product enhancements.

While our ultimate goal is delivering business value, we maintain a strong culture of scientific rigor. If an experiment yields novel, high-quality results, you will have the opportunity and support to publish your findings in top-tier AI conferences (e.g., NeurIPS, ICLR, ACL).

Your profile

Core responsibilities

• Experiment & Build: Design, set up, and execute experiments focusing on LLMs, Agentic AI, model fine-tuning, and broader ML systems. Manage reproducible research pipelines, version code, and data, and select the right frameworks for prototyping.
  Algorithmic Debugging: Actively investigate why a model isn’t converging, why outputs are inconsistent, or why results are unreliable across different ML architectures.
• Code Quality: Write clean, modular code (effective use of classes, functions, and documentation) following strict software engineering best practices.
• Autonomous Delivery: Deliver projects with a high degree of autonomy. Present results clearly, explain the AI behind your findings, and align experiments with team