Senior Machine Learning Engineer - Machine Learning Infrastructure
FlipFull Time
Senior (5 to 8 years)
Candidates must have a minimum of 4+ years of professional experience with a Master's or PhD degree in computer science, machine learning, or a related field, or a minimum of 6+ years of professional experience with a Bachelor's degree. Expertise is required in building production-grade agentic systems and tools, writing production-quality code in Python, and utilizing deep learning frameworks like PyTorch. Familiarity with deploying machine learning models at scale in production environments, writing technical documentation, mentoring, and presenting to technical audiences is also necessary. A proven track record of owning a system or feature and collaborating with multiple teams is essential.
The Staff Machine Learning Engineer will develop state-of-the-art agentic AI systems for triaging, debugging, and solving production issues. They will leverage Sentry's extensive dataset of errors, spans, and profiles to build AI/ML initiatives. This role involves integrating AI and machine learning into core products for issue triage, resolution, and predictive analytics for application performance monitoring.
Full-stack application monitoring and observability
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.