This role focuses on applied research to design and validate domain-specific LLM solutions while building robust evaluation taxonomies
Job Summary
This role focuses on applied research to design and validate domain-specific LLM solutions while building robust evaluation taxonomies.
The successful candidate will develop and maintain knowledge graphs and embeddings to enable semantic search and reasoning capabilities.
Employees are eligible for a comprehensive benefits program including retirement savings plans, insurance coverage, and performance-based incentive compensation.
Matching Summary
This role focuses on applied research to design and validate domain-specific LLM solutions while building robust evaluation taxonomies.
Salary
Base: $90,000 - $157,500 Annual; Bonus/Equity: Eligible for annual performance-based awards; Benefits: Retirement savings plan (401K) with company match, insurance, paid-time off
Skills & Requirements
Must-have
LLM research and fine-tuning experience
Knowledge graph construction with Neo4j
Python proficiency with PyTorch or TensorFlow
Production scale NLP and GenAI implementation
Evaluation framework and taxonomy development
Nice-to-have
Prior work on agentic AI workflows
Experience with cloud platforms AWS Azure GCP
Familiarity with MLOps practices
Low latency serving optimization skills
Collaboration with Platform Engineering teams
Key Requirements
Bachelor's or Master's degree in Computer Science or related field
3+ years of experience in applied machine learning or NLP
Hands-on production scale experience with LLMs and GenAI