Knowledge Engineer / Semantic Expert for AI

Bachelor's degree or equivalent (minimum 12 years' work experience). If Associate’s Degree, must have equivalent minimum 6-year work experience

Minimum of 2 or more of the below Requirements:

Minimum of 2 years of experience in Knowledge Graph technologies (e.g. RDF, SPARQL, LPG, SHACL)

Minimum of 2 years of experience with schema design, ontology management, and Knowledge Graph curation.

Minimum of 2 years of experience in designing and developing knowledge graph solutions and graph-based machine learning models, functional and technical experience required.

Minimum of 1 end-to-end data pipeline implementation for AI applications, particularly those involving LLMs or similar models, including hands-on design and configuration

Minimum of 2 year and strong knowledge of relational databases, object stores, graph databases (e.g. Stardog, Neo4J, Amazon Neptune), and vector databases

2+ years of hands-on experience with cloud platforms (AWS, Azure, GCP)

2+ years of experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)

Practical experience with NLP and/or Search techniques

Prompt engineering, and LLMs for enterprise-scale applications.

You have team lead experience ​

Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.

You have external client-facing consulting experience

Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

Broad experience in diverse ML techniques and agentic systems.

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