Research Engineer

About UkisAI

UkisAI is a Europe-based applied AI lab, founded in 2023. We develop public-facing AI products, run applied research, and work closely with companies to design, prototype, and deploy AI solutions.

Our research is not academic for its own sake. It feeds directly into the models and products we ship, and into the private deployments we run for the companies we work with.

About the role

We are looking for a Research Engineer to help make our models better and smarter. You will work at the point where research meets production: improving how our models are trained, evaluated, and tuned, and turning promising ideas into measurable gains.

You will own experiments end to end, from forming a hypothesis to building the evaluation that proves or kills it. The work is empirical and fast moving, and the results show up in what we ship.

In this role, you will

• Run experiments to improve our models, including fine-tuning, post-training, and data work
• Design and build evaluations that measure model quality on the tasks we actually care about
• Curate, clean, and generate the datasets that training and tuning depend on
• Investigate failures and turn what you learn into concrete improvements
• Work closely with engineering to move research results into products and client deployments

You may be a good fit if you have

• A strong understanding of how modern language models are trained, fine-tuned, and evaluated
• Comfort with Python and the common ML tooling, and the ability to run experiments cleanly and reproducibly
• An empirical mindset: you trust evidence over intuition and build the measurement before drawing conclusions
• Curiosity about why models behave the way they do, and the patience to dig in
• Clear communication of methods and results to both technical and non-technical readers

Strong candidates may also have experience with

• Fine-tuning or post-training open models, including techniques such as LoRA, SFT, or preference-based methods
• Building evaluation suites and benchmarks for language models
• Data pipelines, synthetic data generation, and dataset quality work
• Retrieval, multimodal models, or agentic systems
• Publishing, open-source contributions, or independent research projects

Logistics

This is an internship based in Belgrade, with a hybrid setup. We review applications on a rolling basis.