Senior AI Engineering Lead (PhD)

Required Skills and Experience

- PhD in Computer Science, Machine Learning, Artificial Intelligence, or a highly quantitative field with a strong focus on autonomous systems or NLP. - A senior track record building production agentic systems — real planning, tool use, and multi-step reasoning, not prompt pipelines. Depth counts more than title or exact tenure (roughly 6+ years of software/ML work, or equivalent research-and-shipping depth). - Demonstrated ability to take a technique from current research and land it in a production system, with measured impact. - Deep command of how agents actually work — tool definition, state and context management, orchestration, multi-step control — and the judgment to choose or build the right pattern. (LangGraph, MCP, and whatever replaces them are tools, not the skill.) - Rigorous about evaluation: you ve designed eval harnesses for non-deterministic systems and you trust data over intuition. - Fluent reading and dismantling ML/agent papers; strong Python and system-design fundamentals. - The judgment and communication to help lead a technical team — set direction, review others' work, raise the bar

Why Candidate should apply this position

- Competitive salary (negotiable based on experience) - Build a professional network through collaborations with pharmaceutical companies, industry leaders, and academic experts. - Work on impactful projects that address critical challenges in drug discovery and healthcare. - Employees are entitled to 2 work-from-home days per month, along with daily lunch provided by the company. - Holiday & Tet bonuses; performance-based bonus - Social insurance contribution on full salary