Experiment & Build: Design, set up, and execute experiments focusing on LLMs, Agentic AI, model fine-tuning, and broader ML systems.
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.

A Master's degree (required) in a highly technical and quantitative field such as Mathematics, Physics, Engineering, Computer Science, or a rigorous double degree.
You have zero gaps in your machine learning fundamentals.
Extensive, highly proficient experience with Python and SQL.
Strong track record working with Language Models, Agentic AI workflows, and deep expertise in model fine-tuning (experience with Knowledge Graphs is a plus).
Highly capable of deploying solutions into production environments using tools like Docker and other containerization technologies.
You are exceptionally smart, highly autonomous, and thrive in ambiguity.
You can present complex research results clearly to both highly technical peers and non-technical business stakeholders.

Senior AI Research Engineer – Agents Team

Key skills