Data Scientist Graph AI Engineer

Austin - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Job Description

Overview
We are seeking a Data Scientist / Graph AI Engineer with deep expertise in semantic graph analytics AI-driven anomaly detection and large language models (LLMs). This individual will serve as a technical pioneer designing implementing and validating novel methodologies to transform machine log data into ontology-driven semantic graphs that enable clustering anomaly detection and downstream analytics.
This role demands a thinker builder and innovator who thrives in customer-centric environments can invent intellectual property and can navigate the intersection of data engineering graph representation learning and AI/LLM-based methodology creation.

Required Skills & Experience

Graph Expertise: Strong background in graph databases (Neo4j TigerGraph) graph processing (NetworkX DGL PyTorch Geometric) and ontology modeling (OWL RDF Prot g ).
Machine Learning: Proven experience with graph embeddings anomaly detection clustering and time-series analysis.
AI/LLM Innovation: Hands-on experience applying or extending large language models for data representation semantic reasoning or code generation.
Programming & Engineering: Advanced skills in Python PyTorch/TensorFlow Spark and cloud-native pipelines.
Research & IP Creation: Track record of innovation (patents publications novel algorithms).
Communication: Ability to engage stakeholders with clarity empathy and influence
Experience with Splunk log data or similar enterprise log platforms.
Familiarity with graph-based anomaly detection benchmarks and scalable ML infrastructure.

Job Description Overview We are seeking a Data Scientist / Graph AI Engineer with deep expertise in semantic graph analytics AI-driven anomaly detection and large language models (LLMs). This individual will serve as a technical pioneer designing implementing and validating novel methodologies t...