Job description

WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together youtube.com. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE: Notion has been at the cutting edge of AI since before ChatGPT launched. The job of the Model Capabilities team is to keep us there. We own the model layer of Notion AI: integrating frontier models as they ship, keeping inference reliable and economical at scale, and building new capabilities that other teams take advantage of. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. WHAT YOU'LL ACHIEVE: - Bring new frontier models into production quickly, making them available for our users and our engineers. - Make inference reliable: better error categorization, self-healing retries, and cross-provider failover. - Own observability for the model layer, driving down both time to detection and time to fix. - Build new model-level capabilities and help product teams adopt them. - Act as connective tissue across Notion's AI teams: find the gaps, unblock people, and make sure fixes land with the right owner. SKILLS YOU'LL NEED TO BRING: - Comfort with a moving frontier: The model landscape changes monthly. You keep up with it, form your own view of what's real, and stay pragmatic about what's worth adopting now. - AI fluency as a practitioner: You use AI tools seriously in your own work and have opinions about where they help and where they don't. - Production AI systems experience: You've built and operated systems on top of LLM APIs, not just prototyped with them. You understand token economics, streaming, tool calling, context limits, and how each of these fails in production. - Measurement before conviction: You don't ship a prompt or model change on vibes. You define what "better" means, build or use the evaluation to test it, and are willing to be proven wrong by your own data. - Cost and performance instincts: You treat latency and dollars as product qualities, not afterthoughts, and you can reason about the tradeoff between them and output quality. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $255,000 – $300,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy notion.notion.site and NYLL 144 notion.notion.site. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Requirements

Must-haves

Bring new frontier models into production quickly, making them available for our users and our engineers.
Make inference reliable: better error categorization, self-healing retries, and cross-provider failover.
Own observability for the model layer, driving down both time to detection and time to fix.
Build new model-level capabilities and help product teams adopt them.
Act as connective tissue across Notion's AI teams: find the gaps, unblock people, and make sure fixes land with the right owner.
Comfort with a moving frontier: The model landscape changes monthly. You keep up with it, form your own view of what's real, and stay pragmatic about what's worth adopting now.
AI fluency as a practitioner: You use AI tools seriously in your own work and have opinions about where they help and where they don't.
Measurement before conviction: You don't ship a prompt or model change on vibes. You define what "better" means, build or use the evaluation to test it, and are willing to be proven wrong by your own data.
Cost and performance instincts: You treat latency and dollars as product qualities, not afterthoughts, and you can reason about the tradeoff between them and output quality.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillm

Platform: ashby
Effort: quick