Data Scientist, AI/ML
Core
Improve internet reliability by turning millions of chaos engineering experiments into automated failure analysis and remediation using applied machine learning.
Role type
Senior IC machine-learning engineer (chaos engineering & reliability)
Builds
Intelligent systems for automated failure detection, classification, explanation, and remediation orchestration within the Gremlin Reliability Platform.
Domain
SaaS / Chaos Engineering / Distributed Systems Reliability
Deliverable
production ML models
Required skills
causal inference, graph ML, time-series modeling, reinforcement learning, data pipeline development, feature store construction, model evaluation, distributed systems knowledge
Preferred skills
chaos engineering, site reliability engineering (SRE), agentic AI systems, MLOps tooling, incident management
Technologies
(Not explicitly listed as a tool stack, techniques mentioned)
Responsibilities
Analyze proprietary chaos experiment datasets to identify failure patterns and root causes; Pretrain and fine-tune ML models for automatic failure detection and classification; Build intelligent systems for automated remediation recommendations; Develop scalable data pipelines and feature stores; Collaborate with platform engineers and SREs to integrate AI capabilities into the core product; Research and productionize novel ML approaches like causal AI and agentic systems.
Seniority
Senior, hands-on IC
