AI Scientist, Agentic AI Discovery

Responsibilities

• Evaluate emerging AI techniques
• Reproduce and extend state-of-the-art research approaches
• Build experimental prototypes
• Develop reusable AI system architectures
• Collaborate with cross-functional research and engineering teams

Qualifications

• Education: Master’s degree or higher in AI-related fields, Computer Science, Computational Biology, Bioinformatics, Machine Learning, or related disciplines.
• Experience: At least 3 years of relevant experience in AI, machine learning, or applied research environments.
• AI Engineering Skills: Strong AI engineering and coding skills, with hands-on experience building scalable and production-ready AI applications and systems.
• Agentic AI: Strong interest or hands-on experience in agentic AI systems, multi-agent orchestration frameworks, AI reasoning workflows, and LLM-based applications.
• Biomedical Research: Experience working with biomedical or life science datasets and AI-driven scientific research platforms is highly desirable.
• Generative AI & LLMs: Experience working with modern large language model ecosystems, prompt engineering, retrieval-augmented generation (RAG), or AI workflow orchestration frameworks is a plus.
• Technical Stack: Strong programming skills in Python and familiarity with modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar ecosystems.
• Domain Knowledge: Ability to quickly learn and understand drug discovery and pharmaceutical R&D domains and connect them with AI solutions.
• Other Skills: Strong strategic thinking, problem-solving, interpersonal, and communication skills. Ability to excel in a fast-paced, startup-like environment with a focus on innovation and adaptability.