Applied Science Intern

Key Skills

JAX framework, NeurIPS, Python Programming, PyTorch, Statistical modeling, TensorFlow

Job Description

Your Mission

UiPath is in search of an Applied Science Intern to join our Summer internship program in our Engineering teams in Bucharest, Romania.

As an 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.

Background:

This role is with UiPath advanced machine learning research group. We focus on building large multi-modal models that can take action and move us closer to useful general intelligence. We are machine learning researchers and engineers working to solve the hard problem of getting machines to use software like humans do.

Start date: Summer 2024, 3-months internship

Schedule: full-time

Note: This is a 3-months full-time paid internship. At the end, the successful internship participants will have the possibility to become full-time employees

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.
• Stay up to date with the latest research and technology and communicate your knowledge throughout the company.

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.

Maybe you don’t tick all the boxes above but still think you’d be great for the job Go ahead, apply anyway. 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.