Staff Research Scientist

ServiceNow•Santa Clara, CA

4h•$202,500 - $354,400•Hybrid

About The Position

As a Staff Researcher, you will work on research questions that most AI labs simply do not have access to. ServiceNow AI Research is chartered to build the future of enterprise agentic AI, from a rare vantage point: we see how agents actually behave, inside complex enterprise environments, at scale. You will contribute to research initiatives on how agents accumulate and reuse tacit knowledge, learn and improve continuously, and on their resilience, their safety, and the privacy of the data they handle. These are the real obstacles to enterprise agentic deployment today, and they surface in operational reality well before they appear in the literature. While much of the AI and NLP community concentrates on core agent capabilities, our team explores the dimensions that determine real adoption: safety mechanisms, threat detection, privacy guarantees, and responsible AI practices. You will have the freedom to publish and advance the state of the art, with the rare advantage of testing your hypotheses against real deployments rather than against benchmarks.

Requirements

PhD in computer science, machine learning, or a related field, or equivalent research experience
2 or more years of research experience post-PhD, a significant portion of it in an industrial setting or in direct contact with deployed systems
Established publication record at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP, or equivalents), with contributions recognized as influential in your field
Demonstrated track record of setting/executing research agenda, not only executing one: you have chosen problems before the community turned to them, and you can explain why
Experience working on cross-disciplinary teams or projects collaborating with researchers and engineers
Strong software development skills: you write, maintain, and optimize high-quality research code, and you know what it takes for a result to survive the move into production
Advanced use of agentic tools in your own research practice, and a willingness to advance the team's practices in this area
Demonstrated ability to influence technical decisions beyond your own team, particularly with product and engineering teams
Excellent communication skills, including the ability to explain complex technical work to non-specialist audiences and to executives

Nice To Haves

Expertise in one or more of the following areas: agent memory and tacit knowledge, continual learning, safety and alignment, security and threat detection, privacy, agent evaluation
Experience with AI systems operating in real enterprise environments, with the compliance, governance, and scale constraints that entails
Contributions to open source software, datasets, or evaluation benchmarks used by the community
Scientific service roles: program committees, editorial work, workshop organization
Academic collaborations or supervision of doctoral students

Responsibilities

Contribute to research initiatives on how agents accumulate and reuse tacit knowledge, learn and improve continuously, and on their resilience, their safety, and the privacy of the data they handle.
Explore dimensions that determine real adoption: safety mechanisms, threat detection, privacy guarantees, and responsible AI practices.
Publish and advance the state of the art.
Test hypotheses against real deployments.
Write, maintain, and optimize high-quality research code.
Influence technical decisions beyond your own team, particularly with product and engineering teams.
Explain complex technical work to non-specialist audiences and to executives.