Senior Applied MLE

Accountabilities:

• 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 enable real-time inference.
• Collaborate with data infrastructure engineers to architect a scalable platform supporting complex AI Data Graphs and semantic search.

Requirements:

• MS or PhD in Computer Science or Machine Learning with 4+ years of hands-on experience in NLP, knowledge extraction, or retrieval.
• Proven track record in deploying and maintaining ML models in production environments, specifically using tools like spaCy, GLiNER, or vLLM.
• Strong data manipulation skills using Python, NumPy, and Pandas, and the ability to thrive in a fast-paced startup environment.

Why Apply:

• Work with a founding team of industry veterans and have significant equity and technical ownership.
• Solve the 'hallucination problem' in AI by building context infrastructure for major enterprises.