Senior Applied Scientist, Context Graphs & AI Reasoning

Accrete.AI; Wellesley (MA); Hybrid; USD 160,000 - 210,000; Full time

Benefits offered by this job

Hybrid work schedule

Catered lunches

Professional development

Flexible PTO

Job summary

Accrete.AI in Wellesley, MA is seeking a Senior Applied Scientist to contribute to the research and development behind Accrete's context graphs—the intelligence layer for the Knowledge Engine. You will explore knowledge representation, graph learning, information retrieval, and LLM-driven extraction to reason over complex data and support agentic workflows.

The role emphasizes applying research to scalable systems, with evaluation design and collaboration with engineers and product teams to

Qualifications

• Ph.D. in CS, ECE, or related field with focus on ML/NLP/graph learning.
• Publication record in top venues (NeurIPS/ICML/ACL etc.).
• Experience building extraction pipelines over unstructured data and LLM-based methods.
• Strong programming and system-building skills in Python and PyTorch.

Responsibilities

• Conduct applied research on context graphs, knowledge representation, graph intelligence, and AI systems over complex data.
• Develop architectures to construct and update dynamic context graphs from structured and unstructured data.
• Research entity/relationship/event extraction, provenance, uncertainty, and temporal reasoning.
• Design graph-based representations for entities, relationships, events, and organizational knowledge.
• Develop prototypes and collaborate with engineering to productionize successful research.

Skills

Knowledge representation

Graph ML

NLP

Python & PyTorch

Education

Ph.D. in CS / related field

Tools

Neo4j

PyTorch Geometric

DGL

Python

Job description

Accrete.AI in Wellesley, MA is seeking a Senior Applied Scientist to contribute to the research and development behind Accrete's context graphs—the intelligence layer for the Knowledge Engine. You will explore knowledge representation, graph learning, information retrieval, and LLM-driven extraction to reason over complex data and support agentic workflows.

The role emphasizes applying research to scalable systems, with evaluation design and collaboration with engineers and product teams to