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today
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  • Demandbase

    Applied AI Scientist

    Demandbase · 🇺🇸 San Francisco, CA · posted today
    ApplyFull posting

    Extracted from the posting

    Base
    $206,000 – $310,000
    Remote
    On-site
    Stack
    Argo CD, AWS, Backstage, Crossplane (company stack)

    TL;DR

    Staff-level applied AI scientist, a senior IC who owns research-informed product work on retrieval pipelines, context assembly, and multi-step LLM orchestration and reasoning. The role is a peer to senior technical leaders and works closely with product and engineering, and requires writing production code for LLM and RAG-style and agentic systems. The posting names no specific stack beyond these areas.

    About Demandbase →

    The full posting

    Introduction to Demandbase:

    Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandbase to maximize revenue, minimize waste, and consolidate their data and tech stacks – all in one platform.

    As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have also continuously been recognized as One of The Best Places To Work in the San Francisco Bay Area by Fortune, and One of The 60 Best Companies To Sell For by Selling Power. Our offices are located in San Francisco, New York, Austin, Seattle, India, and the United Kingdom.

    Applied AI Scientist (Staff level)


    About the role
    We're hiring a senior IC who pairs deep research training with the ability to ship. You'll work on hard reasoning, retrieval, and orchestration problems, and you'll take them all the way into the product. This is research-informed product work: novel thinking is expected, but prototypes are the start, not the deliverable. You'll be a peer to our senior technical leaders and a close partner to product and engineering.


    What you'll do

    • Design grounding and context assembly: retrieval pipelines, context selection, query understanding.
    • Improve orchestration and reasoning across multi-step workflows: tool use, routing, decomposition, evaluation.
    • Build structured representations that help the system reason over accounts, people, and activity.
    • Bring research-grade rigor to ambiguous problems, then translate it with engineering into reliable, production-ready capabilities. You won't be a full-time SWE, but you write real code that holds up in production.
    • Raise technical rigor: share patterns, mentor, and accelerate decisions across teams.

    Must have

    • PhD in CS, ML, NLP, IR, or a related field.
    • 7+ years in applied ML, NLP, IR, or ranking (research-track and graduate work can count toward depth), with recent hands-on ownership of LLM and agentic systems.
    • Shipped LLM or RAG-style systems into production and personally owned their reliability, latency, and monitoring at scale.
    • Built and owned agentic or multi-step orchestration (tool use, routing, planning), not just prototypes or demos.
    • Strong coding ability and real comfort in a production codebase.
    • Solid experimentation and evaluation rigor: offline evals, A/B testing, causal thinking.
    • IC5 signals: set technical direction across teams, owned architecture, and operated as a peer-level influence, not just a strong executor.

    Strong plus (any of these stand out, none are required)

    • Knowledge graphs, entity resolution, or representation learning.
    • Query understanding and intent modeling.
    • Search and retrieval depth: lexical, semantic, hybrid, reranking.
    • LLM fine-tuning.
    • A record of taking research from idea to published result to shipped feature.

    You'll do well here if

    • You take a nebulous problem, give it structure, build something testable, and iterate.
    • You're the glue between data science, ML engineering, and product.
    • You explain technical tradeoffs clearly and stay focused on what reaches the customer.

    Our Commitment to Diversity, Equity, and Inclusion at Demandbase

    At Demandbase, we believe in creating a workplace culture that values and celebrates diversity in all its forms. We recognize that everyone brings unique experiences, perspectives, and identities to the table, and we are committed to building a community where everyone feels valued, respected, and supported. Discrimination of any kind is not tolerated, and we strive to ensure that every individual has an equal opportunity to succeed and grow, regardless of their gender identity, sexual orientation, disability, race, ethnicity, background, marital status, genetic information, education level, veteran status, national origin, or any other protected status. We do not automatically disqualify applicants with criminal records and will consider each applicant on a case-by-case basis.

    We recognize that not all candidates will have every skill or qualification listed in this job description. If you feel you have the level of experience to be successful in the role, we encourage you to apply!

    We acknowledge that true diversity and inclusion requires ongoing effort, and we are committed to doing the work required to make our workplace a safe and equitable space for all. Join us in building a community where we can learn from each other, celebrate our differences, and work together.

    Unsolicited Submissions

    At Demandbase, we value thoughtful partnerships and direct connections with candidates. We’re not accepting unsolicited resumes or outreach from third-party recruiting agencies. Any unsolicited submissions will not be reviewed, and no fees will be paid.

    Compensation: $206K - $310K