Staff Applied Scientist - Knowledge Graphs & AI

The role

Design and build knowledge graphs and AI models that power sales execution, including entity resolution, information extraction and graph learning. Work with engineering, product and data teams to take models from prototype to production.

What you will do

• Architect per-tenant knowledge graph schemas, entity resolution, temporal modeling and ontology design for sales execution
• Build NLP pipelines that extract structured knowledge from sales calls, emails and CRM notes
• Design reasoning layers over the knowledge graph for next-best-action, deal risk scoring, coaching and competitive intelligence
• Design and train graph-based models such as GNNs, relational embeddings and link prediction
• Diagnose embedding quality issues, including cold-start entities and temporal drift
• Formalize sales concepts such as deal stages, buyer engagement and account health into structured representations
• Extract ontology structure and lead ontology versioning and migration
• Partner with engineering, product and data teams to bring models to production with reliability and measurable impact

Required qualifications

• PhD in a relevant field such as Computer Science, NLP, Machine Learning or a related discipline
• Focus on knowledge representation, information extraction, graph neural networks, recommendation systems or conversation AI
• Production-quality Python code
• Proficiency in graph databases or query languages such as Neo4j, SPARQL or Cypher
• Ability to turn a vague product goal into concrete technical problems
• Track record of building research prototypes beyond the paper, open-source contributions or real systems projects
• Understanding of monitoring, data drift, latency and operational excellence in production systems
• End-to-end ownership of research and model development with minimal oversight
• Strong communication skills to explain research concepts to cross-functional audiences
• Experience mentoring or leading technical work and driving cross-team technical decisions

Nice to have

• 2+ years applying knowledge graphs or graph-based learning to real-world data in production
• Strong fundamentals in at least two of: knowledge graph construction, information extraction, graph neural networks or recommender systems
• Experience with large-scale unstructured text such as conversational transcripts or email
• Experience with probabilistic graphical models, conversational AI or sales and revenue domain data
• Published research at top-tier venues

Benefits

• Highly competitive salary
• 25 days annual vacation plus sick time and casual leave
• Group medical coverage for employees and up to 5 eligible family members
• OPD benefit covered up to INR 10,000
• Life and personal accident insurance at 3x annual CTC
• 26 weeks of maternity leave pay and 15 days of paternity leave pay
• RSU program
• Diversity and inclusion programs and employee resource groups
• Employee referral bonuses
• Company and team outings

Before you apply

• Outreach invites applicants who do not meet every listed requirement to apply

About the company

Outreach, founded in 2014, is an agentic AI platform for revenue teams. Enterprise customers named in the posting include Databricks, SAP, Siemens and Verizon.