Senior Applied MLE at zaimler.ai
About The Position
Join a high-caliber team building the missing semantic layer for autonomous agents. Working directly with the Chief Scientist (ex-LinkedIn), you will extract knowledge from fragmented enterprise data and build AI Data Graphs. This role is critical for eliminating AI hallucinations and enabling Fortune 500 companies to deploy reasoning agents at scale using proprietary domain intelligence. Why this role is remarkable: Work under a founding team of industry veterans, including the former Chief Architect of Visa and the creator of LinkedIn’s massive Skills Graph. Solve the "hallucination problem" by building context infrastructure that acts as a machine-optimized employee manual for the world's largest enterprises. Join a fast-moving Series A startup already deploying with Fortune 500 leaders in insurance and travel, offering significant equity and technical ownership.
Requirements
- Holds an MS or PhD in Computer Science or ML with 4+ years of hands-on experience in NLP, knowledge extraction, or retrieval.
- Proven track record of deploying and maintaining ML models in production environments, specifically using tools like spaCy, GLiNER, or vLLM.
- Thrives in a fast-paced startup environment and possesses strong data manipulation skills using Python, NumPy, and Pandas.
Responsibilities
- Design and deploy state-of-the-art models to extract structured knowledge and relationships from heterogeneous enterprise data sources.
- Fine-tune Large Language Models (LLMs) and Small Language Models (SLMs) with domain-specific context to power real-time inference.
- Collaborate with data infrastructure engineers to architect a scalable platform that supports complex AI Data Graphs and semantic search.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
