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Salary
≈ $43k – $113k per year (Estimated)
Location
In office (Bucharest)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Apr 24, 2026. UiPath scores A on the Alion truth index.

Overview
Company
Impact
Profile match
UiPath is a Romanian-founded American company started in Bucharest in 2005 that became the leading vendor of robotic process automation, software robots that operate other applications through their user interfaces to automate work no integration existed for. Having grown enormously on that premise, it has spent recent years absorbing the fact that language models can do parts of the same job differently, and has rebuilt its platform around agentic automation that combines deterministic robots with model-driven agents. Headquartered in New York and listed on the New York Stock Exchange, it retains one of the largest installed automation estates in the enterprise market.

Life at UiPath

The people at UiPath believe in the transformative power of automation to change how the world works. 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 a Senior Applied Scientist, you'll work at the intersection between research and product. 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. You need to be kind, courteous, motivated, self-starting, honest and responsible.

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 asym

Maybe you don’t tick all the boxes above-but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes-and passion can’t be learned.

Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected.

We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy.

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