jobs.pl/Oferty pracy/IT - Rozwój oprogramowania/Senior Applied Scientist - Knowledge Graphs & AI
Źródło: CrawlJobs

Senior Applied Scientist - Knowledge Graphs & AI

Outreach Hyderabad, Indie
Pełny etat Praca zdalna

Data publikacji: 30.08.2026

Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. Data is at the core of Outreach's strategy. The mission of the Data Science team is to enable continuous optimization by reconstructing customer engagement workflows from data, developing metrics to measure the success and efficiency of these workflows, and providing tools to support the optimization of these workflows. As a member of the team, you will work closely with other data scientists, machine learning engineers, and application engineers to define and implement our strategy for delivering this mission.

Responsibilities

Knowledge Graph Design & Construction: Design and implement entity resolution and ontology population within established graph schemas; Write and optimize queries for graph traversal and feature extraction; Own data quality for assigned domains; Information Extraction: Build pipelines that extract structured knowledge from unstructured conversational and document data (sales calls, emails, CRM notes), including coreference resolution, relation extraction, and event detection; Run experiments to compare approaches and improve accuracy metrics; Contextual Reasoning & Recommendation: Implement graph traversal logic and feature queries that feed downstream scoring signals; Build and maintain features for deal risk, next-best-action, or coaching recommendation surfaces; Representation Learning: Train and evaluate link prediction and node classification models using established graph embedding methods; Implement evaluation pipelines and track model performance over time; Domain Modeling: Translate sales concepts, such as deal stages, buyer engagement patterns, rep behaviors, and account health, into graph nodes and relationships under the guidance of senior scientists; Contribute to ontology design and documentation; Cross-functional Collaboration: Work with software engineers to deploy models and pipelines into production; Write clean, tested code; Monitor system health and respond to incidents; Participate in code review and design discussions

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 relation extraction, graph neural networks, recommendation systems, or conversation AI and dialogue systems; MS + 2 years of relevant experience will also be considered; Solid engineering fundamentals: production-quality code, clean tested Python code; Experience with graph databases or query languages (e.g., Neo4j, SPARQL, Cypher); Demonstrated ability to build and evaluate ML models; Track record of building things: research prototypes that went beyond the paper, open-source contributions, or side projects that required real systems thinking; Strong Ownership: end-to-end responsibility for research and model development initiatives, from problem formulation and data analysis through experimentation, production deployment, and ongoing performance monitoring; Good communication skills: explain technical concepts to engineers and product managers; Eager to learn: develop deep expertise in knowledge graphs and applied NLP under mentorship of senior scientists.

Nice to have

Hands-on experience applying knowledge graphs or graph-based learning methods to real-world data in a production setting; Strong fundamentals in at least two of: knowledge graph construction, information extraction, graph neural networks, or recommender systems; Experience working with large-scale unstructured text data (conversational transcripts, email, or similar); Experience with probabilistic graphical models, conversational AI, or sales/revenue domain data; Published research at top-tier venues

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
Aplikuj u pracodawcy

Podobne oferty

Wszystkie →

Dostosuj zgody

Każdy cel jest opcjonalny i domyślnie wyłączony. Zgodę możesz wycofać w dowolnym momencie.

Pokazujemy oferty najbliżej Ciebie