AI Research Engineer (LLM/Agentic AI)

TL;DR

AI Research Engineer (LLM/Agentic AI): Designing and executing experiments with LLMs and Agentic AI to build a B2B SaaS decision intelligence platform with an accent on model fine-tuning and algorithmic debugging. Focus on translating research breakthroughs into deployable product enhancements and developing robust E2E MLOps pipelines.

Location: Hybrid in Munich (Note: text explicitly requires legal right to work in Spain)

Company

hirify.global is a B2B SaaS company building an AI-powered decision intelligence app for enterprises.

What you will do

• Design, set up, and execute experiments focusing on LLMs, Agentic AI, and model fine-tuning.
• Investigate and debug complex algorithmic behaviors, such as model convergence and output inconsistency.
• Write clean, modular code and develop extendable E2E research and MLOps pipelines.
• Translate experimental breakthroughs into actionable and deployable directions for Data Science and Product teams.
• Supervise and mentor team members and drive the adoption of research innovations across engineering teams.
• Represent the company's research efforts and publish papers at top-tier AI conferences like NeurIPS, ICLR, and ACL.

Requirements

• Master's degree in Mathematics, Physics, Engineering, Computer Science, or a similar quantitative field.
• Deep mathematical intuition for classical ML, deep learning, and model learning dynamics.
• High proficiency in Python and SQL.
• Extensive experience with Language Models, Agentic AI workflows, and model fine-tuning.
• Ability to deploy solutions into production environments using Docker and containerization.
• Legal right to work in Spain.

Nice to have

• Ph.D. in a relevant technical field.
• Previous experience in academic or industrial AI research labs.
• A track record of publications at top-tier AI/ML conferences or journals.
• Experience with Knowledge Graphs.

Culture & Benefits

• Strong culture of scientific rigor with opportunities to publish in top-tier conferences.
• Work within a small, highly technical, and specialized research team.
• Hybrid work policy with 2 days per week in the office.
• Direct influence on a product aiming to democratize AI in the business world.