Senior AI Engineering Lead (PhD)
Software Development Developer ML AI/Artificial Intelligence AI/ML Machine Learning
年収
Location
Benefits
13ヶ月目の給与
フル社会保険
その他の福利厚生
年間給与の見直し
旅行/会社の旅行
仕事用のノートパソコン/デスクトップ
業績ボーナス
追加の健康保険
Job Overview And Responsibility
NYB is looking for a senior AI engineer leader with the research depth of a scientist and the instincts to lead. You treat our agent as a living research problem, not a shipped feature. The agentic field rewrites its own best practices every few months; we need someone who reads the frontier, has the taste to separate signal from hype, prototypes the promising ideas fast, and lands the ones that hold up in production — with evidence they made the system better. You won't stand up infrastructure from scratch. We already run a working agent orchestrating 300+ scientific tools, with a small, strong team behind it. You're here to make it markedly smarter, more reliable, and more autonomous — and to help lead the engineers building it, raising the bar for how the whole team works. - Own the research-to-production loop for our agent: survey emerging agentic techniques, run structured experiments against them, and ship what proves out. - Continuously upgrade core agent capabilities — planning, tool selection and reasoning, memory, multi-agent coordination — measured against real tasks and bench outcomes, not demos. - Build and own the evaluation harness that tells us whether a change is genuinely an improvement. For a system answerable to experiments, this is the backbone of the role. - Diagnose where the agent fails at the edge of its current capability, and design the fixes. - Help lead the agent platform team: set the technical direction for agentic practice internally, review and mentor, and raise the quality bar for the engineers you work alongside. - Translate frontier research into pragmatic engineering calls under real reliability, latency, and cost constraints.
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
Preferred skills and experiences
- Exposure to scientific or research workflows, ideally drug discovery or another iterative experimental loop. - Prior experience mentoring or setting technical direction for a small team. - Background in RAG, memory systems, or multi-agent orchestration; bio/chem familiarity a plus.
Report to
CEO
Interview process
Screening -> 1-2 rounds of technical interview
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