Senior Applied Scientist - Knowledge Graphs & AI

Ovii's Interpretation of the Role

Senior Applied Scientist leading knowledge‑graph and AI research for revenue‑focused products. Build production‑ready pipelines, graph models, and recommendation features while collaborating with engineers and product teams.

Role Snapshot

• Applied research on knowledge graphs
• End‑to‑end model development
• Production‑grade Python engineering
• Cross‑functional collaboration
• Mentoring junior engineers

Must-Have Requirements

• PhD in Computer Science, NLP, Machine Learning or related field (or MS + 2 years experience)
• Solid engineering fundamentals
• Production‑quality Python code
• Experience with graph databases or query languages (Neo4j, SPARQL, Cypher)
• Ability to build and evaluate ML models
• PhD‑level research in knowledge representation, NLP, ML
• PhD in Computer Science, NLP, Machine Learning or related discipline

Nice-to-Have Signals

• Hands‑on experience applying knowledge graphs in production
• Strong fundamentals in at least two of: knowledge‑graph construction, information extraction, graph neural networks, recommender systems
• Experience with large‑scale unstructured text data
• Experience with probabilistic graphical models, conversational AI, or sales/revenue domain data
• Published research at top‑tier venues
• Production knowledge‑graph projects
• Large‑scale text data processing
• MS with 2+ years relevant experience

Work Setup

• Location: Hyderabad, India
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility specifics

What You'll Likely Work On

• Design and implement entity‑resolution pipelines and ontology population within graph schemas
• Build extraction pipelines for unstructured conversational data, including coreference and relation extraction
• Develop graph‑traversal logic and feature queries that power deal‑risk and next‑best‑action recommendations
• Train and evaluate link‑prediction and node‑classification models using graph‑embedding techniques
• Translate sales concepts into graph nodes/relationships and contribute to ontology documentation
• Collaborate with software engineers to deploy models and pipelines into production, ensuring monitoring and reliability

Good Fit If You Have

• Enjoys turning research prototypes into reliable production systems
• Strong ownership mindset with minimal supervision
• Effective at explaining technical ideas to engineers and product managers