Applied AI Scientist

Applied AI Scientist 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. About the Role: We’re hiring an AI Scientist to help us build the next generation of AI features that show up directly in the product and improve customer outcomes. You’ll work on reasoning, planning, context and knowledge engineering problems, design the “brains” behind how our system finds the right context, and make our orchestration smarter and more reliable. This is a senior individual contributor role (IC5 / Staff Data Scientist level). You’ll be a peer to other senior technical leaders and a close partner to product and engineering. Responsibilities - Design approaches for grounding and context assembly (retrieval pipelines, context selection, query understanding). - Improve AI orchestration and reasoning quality across multi-step workflows (tool use, routing, decomposition, evaluation). - Develop and iterate on knowledge context graphs or other structured representations that help the system reason over accounts, people, and activity. - Partner closely with engineering teams to translate prototypes into reliable, production-ready product capabilities. - Raise technical rigor within the team by sharing patterns, mentoring others, and accelerating decision-making processes. - Partner with engineering to turn prototypes into reliable product capabilities. You won’t need to be a full-time SWE, but you should be comfortable writing real code that holds up. Qualifications CORE EXPERIENCE & TECHNICAL BACKGROUND - Deep Domain Expertise: 7+ years of relevant experience (or equivalent depth) in NLP, information retrieval, ranking, applied ML, and agentic application architecture and design. - Experience with Knowledge Graphs, entity resolution, or representation learning. - Experience building systems that operate at scale, specifically regarding latency, reliability, and monitoring. - Prior work on orchestration frameworks, agentic workflows, or multi-step reasoning systems. - A strong background in one or more of the following areas: - LLM Applications: Practical experience with grounding, RAG-style systems, tool use, and routing, planning. - Query Understanding: Experience with intent modeling. - Search and Retrieval: Including lexical, semantic, hybrid retrieval, and reranking. - Strong coding ability and comfort working with production codebases. - Solid grounding in statistics and experimentation, including offline evaluations, A/B testing, and causal thinking. EXECUTION & SOFT SKILLS - Problem-Solving: The ability to take a nebulous problem, create structure, build something testable, and iterate. - Collaborative Mindset: Comfortable acting as the "glue" between data science, ML engineering, and product teams. - Communication: The ability to explain technical tradeoffs clearly and a focus on solutions that effectively reach customers. Benefits Our benefits include options for up to 100% paid Medical and Vision premiums for employees, a flexible PTO policy, paid holidays, and access to mental health and wellness resources. We also provide a 401(k) with pre-tax, after tax, and roth options, as well as short- ... (truncated, view full listing at source)