Machine Learning Research Scientist

About the role

Sentra is building organizational superintelligence through a memory infrastructure that reasons across time, causality, and context. As a Machine Learning Research Scientist you will tackle fundamental problems in knowledge representation, temporal reasoning, and semantic compression, turning raw event streams into durable organizational knowledge.

Key responsibilities

• Build LLM‑powered information extraction pipelines that convert unstructured communications into structured entity‑relationship graphs.
• Develop memory consolidation algorithms that validate information across observations, merge duplicate entities, and prune transient data.
• Design temporal knowledge‑graph architectures that model organizational execution state as continuously updated living systems.
• Create graph‑attention mechanisms and reasoning systems for complex causal queries about blockers, dependencies, and outcome patterns.
• Research lossy semantic compression using information‑theoretic principles to condense event streams into query‑relevant long‑term memory.

Required profile

• 5+ years building novel systems in machine learning, NLP, knowledge graphs, or related areas, demonstrated through publications, production implementations, or significant open‑source contributions.
• Deep knowledge of knowledge graphs, graph neural networks, or temporal reasoning, proven by shipped systems and architectural exploration.
• Strong foundation in ML and NLP, especially information extraction, entity resolution, and semantic representation.
• Proficiency in Python and modern ML frameworks (PyTorch preferred) with experience deploying models at scale.
• Track record of publishing research (conference papers, technical blog posts, or detailed documentation) and translating novel architectures into production.
• Ability to move between theoretical investigation and practical implementation, shipping research into real‑world products.

Required skills

• Python
• PyTorch
• Graph neural networks
• Knowledge graphs
• Temporal reasoning
• Neo4j, TigerGraph, Neptune (graph databases)
• Federated learning
• Differential privacy

What we offer

• Base salary $150,000 – $300,000 per year.
• Equity ranging from 0.3 % to 2 %.
• Comprehensive health coverage (medical, dental, vision).
• Wellness & productivity stipend of $2,500 per month.
• Latest MacBook Pro and AI development tools (ChatGPT Pro, Claude Pro, Cursor, etc.).
• Dedicated budget for conferences, courses, and professional development.
• Relocation support for on‑site hires.
• Flexible time‑off policy.