Staff Applied Scientist Knowledge Graphs & AI Agents Remote

Loopio Inc.; United States; Remote; USD 42,000 - 73,000; Full time

Benefits offered by this job

Remote-friendly policy

Job summary

Loopio is seeking a Staff Applied Scientist to lead the science behind knowledge graphs and agent systems that power our AI-enabled products. You will own technical direction, mentor senior talent, and shape applied ML practices across teams.

You’ll collaborate with teams across Canada, the UK, and India, and work remotely from India with overlapping global hours. Expect a strong focus on RAG, LLM fine-tuning, and robust evaluation strategies.

Qualifications

• 8+ years applying ML in production.
• Strong background in NLP and LLMs with RAG experience.
• Experience finetuning LLMs and classical ML.
• Track record of designing evaluations to guide releases.
• 3+ years building knowledge graphs in production (ontology design, information extraction, entity resolution).
• 3+ years building LLM-based agents in production (planning, tool use, orchestration).
• Strong Python and software engineering skills; able to ship ML services.
• Ability to communicate trade-offs in customer value terms.

Responsibilities

• Design and build knowledge graphs turning unstructured content into structured knowledge.
• Build agents and retrieval systems that find, check, and use knowledge.
• Use user feedback to keep knowledge accurate and improve results.
• Define quality metrics and decide what features to ship.
• Set technical direction and collaborate with product and other AI teams.
• Mentor engineers and data scientists; set experimentation standards.

Skills

Knowledge graphs

LLMs

NLP

Production ML

Python

RAG

Mentoring

Education

PhD or MS in CS/ML

Tools

Neo4j

Cypher

Job description

Loopio is seeking a Staff Applied Scientist to lead the science behind knowledge graphs and agent systems that power our AI-enabled products. You will own technical direction, mentor senior talent, and shape applied ML practices across teams.

You’ll collaborate with teams across Canada, the UK, and India, and work remotely from India with overlapping global hours. Expect a strong focus on RAG, LLM fine-tuning, and robust evaluation strategies.