Staff Applied Scientist - Knowledge Graphs & AI
New
HyderabadFull-TimeStaff
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 2+ years of hands-on experience applying knowledge graphs or graph-based learning methods to real-world data in a production setting.
- Required Skills
- PythonMachine LearningNLP
Requirements
- PhD in Computer Science, NLP, Machine Learning, or related discipline with a focus on knowledge representation, information extraction, graph neural networks, or recommendation systems.
- Proficiency in Python and graph databases or query languages (e.g., Neo4j, SPARQL, Cypher).
- Strong engineering fundamentals with the ability to write production-quality code.
- Track record of building things, including understanding the gap between research prototypes and reliable production systems.
- Experience with monitoring, data drift, latency, and operational excellence.
- Strong ownership of end-to-end model development from problem formulation to production deployment.
- Ability to translate research concepts into product impact for cross-functional audiences.
- Experience mentoring or leading technical work.
- 2+ years of hands-on experience applying knowledge graphs or graph-based learning methods to real-world data in a production setting (preferred).
- Experience working with large-scale unstructured text data such as conversational transcripts or email (preferred).
Responsibilities
- Architect and evolve per-tenant knowledge graph schemas including entity resolution, temporal modeling, and ontology design.
- Architect NLP pipelines to extract structured knowledge from unstructured conversational and document data.
- Design reasoning and inference layers over the knowledge graph for next-best-action suggestions, deal risk scoring, and coaching recommendations.
- Design and train graph-based models (GNNs, relational embeddings, link prediction) over heterogeneous, multi-relational structures.
- Formalize sales execution concepts into structured representations and lead ontology versioning and migration.
- Partner with engineering, product, and data teams to bring models from prototype to production.
View Full Description & ApplyYou'll be redirected to the employer's site
