Intern - AI Engineering

Overview

The AI Engineer Intern will support the design and implementation of AI-driven solutions for pharmaceutical and biotech applications, with a focus on drug discovery. This internship offers hands‑on experience in applying artificial intelligence to real‑world R&D challenges while working alongside experienced scientists and engineers. The intern will gain exposure to the drug discovery process and contribute to projects that explore how AI can improve efficiency and innovation.

• Architect and manage agent‑based systems that collaborate to execute drug discovery workflows
• Coordinate multiple AI agents (e.g., PI, modeling, simulation, optimization, critic) to enable automated discovery
• Assist in identifying opportunities within drug discovery where AI can enhance processes and outcomes
• Support the development and implementation of machine learning and deep learning models for research applications
• Reproduce and evaluate existing AI models and research papers to understand their applicability
• Help adapt and optimize AI solutions for new use cases within R&D workflows
• Contribute to building scalable and practical AI tools under guidance from senior team members
• Stay current with emerging AI trends and technologies and share insights with the team
• Collaborate with cross‑functional teams to understand scientific problems and translate them into AI‑driven approaches

• Currently pursuing a Bachelor’s, Master’s or PhD degree in Computer Science, Artificial Intelligence, Data Science, Bioinformatics, or a related field
• Experience with LLMs, agent frameworks, or workflow orchestration tools (e.g., Lang Chain, Auto Gen, Bio Nemo, etc.)
• Familiarity with coding tools (e.g., Codex, Claude Code, etc.)
• Interest in pharmaceutical or biotech applications, particularly drug discovery
• Experience with academic or personal AI/ML projects
• Exposure to analyzing or reproducing research papers
• Coursework or projects related to life sciences, bioinformatics, or computational biology
• Strong analytical and problem‑solving skills
• Willingness to learn and adapt in a fast‑paced, innovative environment
• Effective communication and teamwork skills
• Ability to translate technical concepts into practical applications
• Prior experience in drug discovery or AI research is a plus but not required
• Professional‑level English communication skills are preferred