AI Reliability Engineer
1 day ago
Role Overview
This position plays a pivotal role in driving AI reliability, ensuring that AI features and services meet the highest standards of performance, robustness, and reliability.
A key focus area is building and managing high-performing engineering teams specializing in AI system reliability. This entails leading efforts to detect, diagnose, and mitigate failures and degradation across AI features in production.
The ideal candidate will have expertise in AI feature development lifecycles, data pipelines, model debugging, and post-deployment validation. Additionally, they should possess strong problem-solving skills, with experience in root cause analysis, reliability engineering, or debugging complex distributed systems.
Key Responsibilities:
- Develop and implement strategies to enhance monitoring, observability, and data quality.
- Design and deploy tools, dashboards, and processes to surface anomalies, performance regressions, and edge cases.
- Oversee data analysis, annotation processes, and AI system workflows to improve model performance.
Requirements:
- 2+ years of experience managing high-performing engineering teams, preferably in AI, ML infrastructure, or production systems.
- Strong understanding of AI/ML concepts, including data pipelines, model training, and deployment.
- Proven track record of success in root cause analysis, reliability engineering, or debugging complex distributed systems.
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