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.

You'll design grounding and context assembly: retrieval pipelines, context selection, query understanding. You'll improve orchestration and reasoning across multi-step workflows: tool use, routing, decomposition, evaluation. You'll build structured representations that help the system reason over accounts, people, and activity. You'll 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. You'll raise technical rigor: share patterns, mentor, and accelerate decisions across teams.

Responsibilities

• 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.
• Raise technical rigor: share patterns, mentor, and accelerate decisions across teams.

Requirements

• 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.
• Strong 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.
• 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.

Qualifications

• 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).
• 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.
• Strong 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.
• 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.

Skills

• Strong coding ability and real comfort in a production codebase.
• Strong 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.
• 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.

Benefits

• Our commitment to diversity, equity, and inclusion at Demandbase.
• Unsolicited Submissions policy.

Pay

Competitive salary commensurate with experience.

Schedule

Hybrid work schedule.

Company Information

Our offices are located in San Francisco, New York, Austin, Seattle, India, and the United Kingdom.

Equal Opportunity Employer

We are committed to 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.