Applied Scientist II

Bucharest, RomaniaHybrid

Requirements

LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works.
You'll build, optimize and deploy machine learning models as well as scale them up.
We’re looking for people who love machine learning and computer science, are interested in the theory behind the models, and are motivated to solve real world problems with techniques that are scalable, efficient, and reliable in production.
The ideal candidate is someone wanting to prove and better themselves in a fast-paced machine learning group.
WHAT YOU'LL DO AT UIPATH - Build and improve modern machine learning models to solve complex ML problems. - Read papers, propose model improvements, implement and test the new models. - Think about the best human-computer interfaces to make machine learning models accessible to everyone. - Run regular benchmarks and perform statistical analysis, draw conclusions on the impact of your research-based optimizations and present your findings to the team.
WHAT YOU'LL BRING TO THE TEAM - Knowledge of Python and modern ML libraries like PyTorch, Tensorflow, or JAX. - Ability to implement models from academic papers like ICML, ICLR, NeurIPS, etc. - Strong quantitative intuition and mastery of linear algebra, probability and statistics. - Solid knowledge of basic data structures (list, vector, stack, heap), basic algorithms (sort, search, etc.) and associated time/memory asymptotic complexity.

We’re committed to creating category-leading enterprise software that unleashes that power.
To make that happen, we need people who are curious, self-propelled, generous, and genuine.
People who love being part of a fast-moving, fast-thinking growth company.
And people who care—about each other, about UiPath, and about our larger purpose.
Could that be you? YOUR MISSION As an applied scientist, you'll work at the intersection between research and product.
You need to be kind, courteous, motivated, self-starting, honest and responsible.
Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please.