Staff Research Scientist

Description

The company's AI research group builds enterprise agentic AI and observes how agents behave in complex enterprise settings at scale.

The work tackles questions most AI labs cannot access, because the team sees agents operating in real enterprise environments.

Research topics include how agents build and reuse tacit knowledge, how they keep learning, and their resilience, safety, and data privacy. These are the main barriers to enterprise adoption and appear in production before they appear in papers.

The team focuses on what determines real adoption: safety mechanisms, threat detection, privacy guarantees, and responsible AI. You are free to publish, and you can test hypotheses against live deployments rather than only benchmarks.

Responsibilities

• Contribute to research on how agents accumulate and reuse tacit knowledge and how they improve over time.
• Contribute to research on agent resilience, safety, and the privacy of the data agents handle.

Requirements

• Hold a PhD in computer science, machine learning, or a related field, or have equivalent research experience.
• Have 2+ years of research experience after your PhD, much of it in industry or directly with deployed systems.
• Have a strong publication record at top venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or equivalents, with work recognized as influential.
• Have set and carried out your own research agenda, choosing problems before the community focused on them, and be able to explain why.
• Have worked on cross-disciplinary teams alongside researchers and engineers.
• Write, maintain, and optimize high-quality research code, and understand what a result needs to hold up in production.
• Use agentic tools heavily in your own research and help the team improve its practices with them.
• Influence technical decisions beyond your own team, especially with product and engineering teams.
• Communicate complex technical work clearly to non-specialists and executives.
• Have expertise in one or more of: agent memory and tacit knowledge, continual learning, safety and alignment, security and threat detection, privacy, or agent evaluation.
• Have experience with AI systems in real enterprise environments, including the compliance, governance, and scale constraints that come with them.
• Have contributed open source software, datasets, or evaluation benchmarks that the community uses.
• Have served in scientific roles such as program committees, editorial work, or workshop organization.
• Have collaborated academically or supervised doctoral students.

Conditions

For this location, base pay is $202,500 - $354,400, plus equity when applicable, variable incentive compensation, and benefits.

Sales positions generally offer a competitive On Target Earnings incentive structure.

The base pay shown is a guideline. Individual total compensation depends on qualifications, skill level, competencies, and work location, and compensation is based on the location where the role sits and may change.

Work personas (flexible, remote, or required in office) are assigned based on the nature of the work and the assigned work location.

To determine eligibility for a work persona, the company may check the distance between your primary residence and the nearest office using a third-party service.

Benefits

• Health plans, including flexible spending accounts.
• 401(k) plan with company match, ESPP, matching donations, a flexible time away plan, and family leave programs.