Outreach
1001 - 5000 employees
Founded 2014
🤖 Artificial Intelligence
🏢 Enterprise
Artificial Intelligence • Sales • Enterprise
Outreach is a company that provides an AI-powered sales execution platform designed to streamline workflows and enhance the effectiveness of sales representatives. The platform utilizes artificial intelligence to forecast revenue accurately, manage deals, and optimize the entire sales process. Outreach helps sales teams prioritize tasks, identify prospects, and maintain engagement throughout the customer lifecycle, ultimately aiming to boost win rates and reduce churn. With over 6,000 global customers, Outreach focuses on transforming seller workflows to consistently exceed revenue targets.
Staff Applied Scientist – Knowledge Graphs, AI
🔥 0 minutes ago
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Outreach
1001 - 5000 employees
Founded 2014
🤖 Artificial Intelligence
🏢 Enterprise
Artificial Intelligence • Sales • Enterprise
Outreach is a company that provides an AI-powered sales execution platform designed to streamline workflows and enhance the effectiveness of sales representatives. The platform utilizes artificial intelligence to forecast revenue accurately, manage deals, and optimize the entire sales process. Outreach helps sales teams prioritize tasks, identify prospects, and maintain engagement throughout the customer lifecycle, ultimately aiming to boost win rates and reduce churn. With over 6,000 global customers, Outreach focuses on transforming seller workflows to consistently exceed revenue targets.
📋 Description
• Knowledge Graph Design & Construction: Architect and evolve per-tenant knowledge graph schemas, including entity resolution, temporal modeling, and ontology design tailored to sales execution domains. • Information Extraction: Architect NLP pipelines that extract structured knowledge from unstructured conversational and document data (sales calls, emails, CRM notes), including coreference resolution, relation extraction, and event detection. • Contextual Reasoning & Recommendation: Design reasoning and inference layers over the knowledge graph to power next-best-action suggestions, deal risk scoring, coaching recommendations, and competitive intelligence surfaces. • Representation Learning: Design and train graph-based models (GNNs, relational embeddings, link prediction) over heterogeneous, multi-relational graph structures to support downstream reasoning and retrieval tasks. Diagnose and address embedding quality issues including cold-start entities, and temporal drift. • Domain Modeling: Formalize sales execution concepts such as deal stages, buyer engagement patterns, rep behaviors, and account health, into structured representations that ground the platform's AI capabilities. Extract ontology structure. Lead ontology versioning and migration. • Cross-functional Collaboration: Partner with engineering, product, and data teams to bring models from prototype to production, ensuring reliability and measurable impact at scale.
🎯 Requirements
• PhD in a relevant field such as Computer Science, NLP, Machine Learning, or a related discipline with a focus on knowledge representation and reasoning, information extraction and relationship extraction, graph neural networks, recommendation systems, or conversation AI and dialogue systems. • Strong engineering fundamentals. You can write production-quality code, not just prototype notebooks. Proficiency in Python; and graph databases or query languages (e.g., Neo4j, SPARQL, Cypher) is required. • Comfort with ambiguity. You can take a vague product goal and decompose it into concrete technical problems. You don't need a fully scoped spec to start making progress. • A track record of building things: whether that's research prototypes that went beyond the paper, open-source contributions, or side projects that required real systems thinking. You understand the gap between a research prototype and a reliable production system, such as monitoring, data drift, latency, and operational excellence. • Strong Ownership: Take end-to-end responsibility for research and model development initiatives, from problem formulation and data analysis through experimentation, production deployment, and ongoing performance monitoring, driving outcomes with minimal oversight. • Strong communication skills with the ability to translate research concepts into product impact for cross-functional audiences. • Experience mentoring or leading technical work. You've helped junior team members grow and have driven cross-team technical decisions.
🏖️ Benefits
• Highly competitive salary • 25 days annual vacation time + sick time and casual leave • Group medical policy coverage available to employees and up to 5 eligible family members • OPD benefit covered up to INR 10,000 • Life insurance and personal accident insurance at 3x annual CTC • 26 weeks of maternity leave pay, and 15 days of paternity leave pay • Opportunity to be part of company success via the RSU program • Diversity and inclusion programs that promote employee resource groups like OWN+ (Outreach Women's Network), Adelante (Latinx community), OBX (Outreach Black Connection), Mosaic (AAPI community), Pride (LGBTQIA+), Gender+, Disability Community, and Veterans/Military • Employee referral bonuses to encourage the addition of great new people to the team • Fun company and team outings because we play just as hard as we work
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