We're looking for a motivated engineering student to join our AI team and help build solutions for our global client base.

We're a small team (not including the bots) of AI enthusiasts who love to work on challenging projects involving Machine Learning, LLM Engineering, Data Engineering, and everything else data or AI-related. We often collaborate with DevOps, Backend, QA, and System Architect teams and have delivered AI-powered solutions for industries like smart devices, hospitality, and healthcare.

Our tech stack depends on the project, but we mostly use Python and its community-powered libraries and frameworks. We're excited about creating novel approaches for yet unsolved problems, automating jobs that usually consume too much time, and using cloud technologies to scale everything up. 

Requirements

Qualifications & Experience

• Studying computer science, engineering, natural sciences, or a related field, available to work full-time (40h/week)
• Solid grasp of at least one programming language, ideally Python
• You've actually used AI tools to build something — not just prompted ChatGPT for homework, but built, debugged, or shipped something using an LLM
• Hands-on experience building LLM-powered applications
• Comfort adapting to cross-functional teams and new ways of working
• You use AI tools daily and know when to trust them and when not to — you understand that AI can speed up the work, but the thinking, architecture, and judgment behind a solution are still yours
• Strong written and spoken English, since you'll work directly with international clients

Your responsibilities

You'll spend most of your time reasoning about AI systems rather than typing out boilerplate. You'll be designing, testing, and evaluating LLM-powered features where "correct" depends on context, not a fixed formula.

• Designing and evaluating LLM-based features, including building test cases for non-deterministic behavior
• Reviewing, refining, and shipping AI-assisted code that's clean, maintainable, and genuinely production-ready — not just a good demo
• Rolling out features and iterating based on feedback from QA engineers, users, and clients
• Working directly with cross-functional teams (DevOps, Backend, QA, System Architects) and, at times, with clients themselves
• Participating in code reviews, pairing, and knowledge-sharing — you'll learn as much from explaining your reasoning as from writing code
• Presenting your solutions to colleagues and, when relevant, to clients