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Staff Machine Learning Engineer, AI

Sentry · San Francisco, California

RemoteStaffData and MLEngineeringEngineeringPosted 12 months ago
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About this role

ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE ROLE As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. IN THIS ROLE YOU WILL - Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues - Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles - Own the development of major initiatives in the AI/ML space YOU'LL LOVE THIS JOB IF YOU - Are driven by impact and enjoy working on high-stakes, high-visibility projects - Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members - Thrive in cross-functional teams and enjoy building features alongside developers and product teams QUALIFICATIONS - Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field - Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field - Demonstrated expertise building production-grade agentic systems and tools - You are comfortable writing production quality code (we use Python) - Expertise with deep learning frameworks (we use PyTorch) - Familiarity in deploying machine learning model

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