Applied Scientist Intern (AI)

TL;DR

Applied Scientist Intern (AI): Designing and implementing state-of-the-art machine learning and generative AI solutions to solve complex business problems with an accent on end-to-end system development. Focus on creating new algorithms, writing technical white papers, and deploying production-level projects.

Location: Onsite in Cairo, Egypt, or other EMEA locations (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, UK). Not remote.

Company

hirify.global AI is a global leader in integrating advanced machine learning and artificial intelligence into consumer and business products.

What you will do

• Design and develop end-to-end AI systems and production-level projects.
• Invent and implement state-of-the-art solutions for complex, unsolved problems.
• Create new algorithms and models to support hirify.global Science.
• Write technical white papers and define project roadmaps.
• Collaborate with experienced scientists to deploy models into production.

Requirements

• Enrolled in a PhD or Master's degree in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or related fields.
• Proficiency in programming languages such as Python, Java, or C++.
• Ability to work onsite at one of the specified EMEA locations.

Nice to have

• Publications at top-tier peer-reviewed conferences or journals.
• Experience implementing algorithms using toolkits and self-developed code.
• Experience solving business problems via machine learning, data mining, and statistical algorithms.

Culture & Benefits

• Competitive stipend/salary.
• Dedicated mentorship from experienced managers and scientists.
• Opportunities to publish original research at top-tier conferences.
• Access to professional networking events within the hirify.global Science community.
• Supportive and inclusive culture with workplace accommodations.

Hiring process

• Applications reviewed on a rolling basis.
• Assignment to teams based on research interests and experience.
• Technical interviews following team alignment.