Senior Applied Scientist: Dynamic Context Graphs & AI

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

Benefits offered by this job

Competitive Salary

Comprehensive Insurance

401(k) Plan

Flexible PTO & Hybrid Work

Growth & Development

Onsite Perks

Team Bonding

Job summary

Accrete is seeking a Senior Applied Scientist to advance its context graphs—the intelligence layer powering the Knowledge Engine and its agents.

You will work on knowledge representation, graph-based ML, and information retrieval, integrating LLMs with graph structures while ensuring rigorous evaluation and production readiness.

This hybrid role involves collaboration with engineering and product teams, and a three-day-in-office schedule in Wellesley, MA.

Qualifications

• Ph.D. in CS/EE/ computational linguistics or related field with ML/NLP focus.
• Research depth in knowledge representation, graph learning, information extraction or retrieval.
• Peer-reviewed publications in NeurIPS/ICML/ACL/EMNLP/KDD/WWW/ISWC.
• Experience building extraction pipelines over unstructured data and LLM-based extraction.
• Experience designing evaluation for problems without clean ground truth.

Responsibilities

• Conduct applied research on context graphs, knowledge representation, graph intelligence, and AI systems over heterogeneous data.
• Develop algorithms for constructing and updating dynamic context graphs from structured and unstructured data.
• Research entity/relationship/event extraction, temporal reasoning, and semantic linking across sources.
• Develop graph representations of entities, relationships, events, decisions, and organizational knowledge.
• Explore time, provenance, uncertainty, and source attribution in graph representations.
• Design graph methods to support LLM reasoning, retrieval, planning, and agentic workflows.
• Combine LLMs with structured graphs to improve grounding and explainability.
• Design benchmarks and evaluation frameworks for graph quality and retrieval performance.
• Translate research into scalable production with engineering teams.
• Publish technical results and contribute to IP and documentation.

Skills

Python

PyTorch

Graph databases

Neo4j

Graph learning

NLP

Information retrieval

LLMs

Prototyping

Education

Ph.D. in Computer Science or related field

Tools

PyTorch Geometric

DGL

Neo4j

LLM tooling

Job description

Accrete is seeking a Senior Applied Scientist to advance its context graphs—the intelligence layer powering the Knowledge Engine and its agents.

You will work on knowledge representation, graph-based ML, and information retrieval, integrating LLMs with graph structures while ensuring rigorous evaluation and production readiness.

This hybrid role involves collaboration with engineering and product teams, and a three-day-in-office schedule in Wellesley, MA.