Intern - AI Engineering at SK Life Science, Inc. in Paramus, NJ

Summary: SK Life Science, Inc. is focused on developing AI-driven solutions for pharmaceutical and biotech applications. The AI Engineer Intern will support the design and implementation of AI solutions for drug discovery, gaining hands-on experience while collaborating with experienced scientists and engineers. Responsibilities: - 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 Required Qualifications: - 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., LangChain, AutoGen, BioNemo, 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, bi - 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 Preferred Qualifications: - Prior experience in drug discovery or AI research is a plus but not required - Professional-level English communication skills are preferred Required Skills: Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models, Agent Frameworks, Workflow Orchestration Tools, Coding Tools, Bioinformatics, Computational Biology, Drug Discovery, Analytical skills