Data Scientist
2 days ago
Location: Austin, TX/ Cupertino, CA (Hybrid)
Market Rate
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, Protégé).
- 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.
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