Machine Learning Research Scientist at Sentry

San Francisco, California, United States

Apply Now

$120,000 – $300,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

TechnologyIndustries

Requirements

5+ years building novel systems in machine learning, NLP, knowledge graphs, or related areas with evidence through publications, production implementations, or significant open-source contributions
Deep knowledge of knowledge graphs, graph neural networks, or temporal reasoning demonstrated through shipped systems and architectural exploration
Strong ML and NLP foundation, particularly in information extraction, entity resolution, or 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 technical documentation) and exploring novel architectures
Ability to move between theoretical investigation and practical implementation, shipping research into production

Responsibilities

Build LLM-powered information extraction pipelines that process unstructured communications and text data into structured entity-relationship representations
Develop memory consolidation algorithms that validate information through multiple observations, merge duplicate entities, and prune ephemeral data
Design temporal knowledge graph architectures that model organizational execution state as living, continuously updated systems rather than static records
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
Design entity resolution systems handling identity evolution where entities merge, split, and transform through time
Build meta-learning systems that identify organizational patterns and recognize when current situations match historical success or failure indicators
Develop privacy-preserving cross-organizational learning using federated learning and differential privacy techniques
Publish research findings and contribute to the broader research community on knowledge graphs and organizational intelligence

Skills

Key technologies and capabilities for this role

Machine LearningNLPKnowledge GraphsLLMGraph AttentionEntity ResolutionFederated LearningDifferential PrivacyMeta-LearningTemporal Reasoning

Questions & Answers

Common questions about this position

What is the salary range for the Machine Learning Research Scientist position?

The salary range is $120K - $300K.

Is this position remote or onsite?

The position is onsite.

What are the must-have skills for this role?

Must-have skills include 5+ years building novel systems in machine learning, NLP, knowledge graphs or related areas; deep knowledge of knowledge graphs, graph neural networks, or temporal reasoning; strong ML and NLP foundation in information extraction, entity resolution, or semantic representation; proficiency in Python and modern ML frameworks like PyTorch; and a track record of publishing research.

What does the company do, and what is the work environment like?

Sentra is building organizational superintelligence through memory infrastructure that reasons across time, causality, and context. The role involves tackling fundamental problems in knowledge representation, temporal reasoning, and semantic compression in a research-focused environment.

What makes a strong candidate for this Research Scientist role?

Strong candidates have 5+ years of experience building novel ML/NLP/knowledge graph systems with publications or production work, deep expertise in knowledge graphs or temporal reasoning through shipped systems, proficiency in Python/PyTorch, and the ability to ship research into production.

Sentry

Full-stack application monitoring and observability

About Sentry

Sentry offers full-stack application monitoring and observability, providing deep context, session replay, and distributed tracing to identify errors and performance bottlenecks across frontend and backend technologies, supporting JavaScript, Python, PHP, and more.

San Francisco, CaliforniaHeadquarters

2011Year Founded

$210.6MTotal Funding

SERIES_ECompany Stage

Consumer Software, Enterprise SoftwareIndustries

201-500Employees

Benefits

Competitive Compensation + Equity

401(k) Plan

Medical, Dental, Vision Insurance

Commuter Stipend

Professional Development Stipend

Health & Wellness Benefits

Charitable Matching Program

Flexible PTO

Paid Parental Leave

Risks

Competition from AI-powered tools like Devnaut may impact Sentry's market share.

The Functional Source License might deter developers preferring permissive open-source licenses.

Expanded integrations in Google's Gemini 2.0 could increase competition in error tracking.

Differentiation

Sentry offers real-time error tracking across the entire software stack.

The Functional Source License protects Sentry's commercial interests while supporting open-source collaboration.

Sentry's integration with Google's Gemini 2.0 enhances its visibility among developers.

Upsides

Integration with AI tools like Devnaut boosts Sentry's codebase visibility and productivity.

Sentry's focus on mobile performance monitoring aligns with growing demand in mobile solutions.

Winning the 2023 Digital Innovator Award highlights Sentry's leadership in digital transformation.

Land your dream remote job 3x faster with AI

Try Jobo Free