Staff Machine Learning Engineer, AI
SentrySan Francisco, California$210k – $280kPosted 23 February 2026
Job Description
About SentryBad software is everywhere, and we’re tired of it. Sentry is on a mission to help developers write better software faster so we can get back to enjoying technology.With more than $217 million in funding and 100,000+ organizations that believe we’re on to something, we're building performance and error monitoring tools that help companies like Disney, Microsoft, and Atlassian spend less time fixing bugs and more time building products.Sentry embraces a hybrid work model across our global hubs, with Mondays, Tuesdays, and Thursdays set as in-office anchor days to encourage meaningful collaboration. If you like to selfishly build things that make your digital life better, come help us build the next generation of software monitoring tools.About the roleAs 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 willBuild state-of-the-art agentic AI systems to triage, debug, and solve real production issuesLeverage Sentry’s novel (and massive) dataset of errors, spans, and profilesOwn the development of major initiatives in the AI/ML spaceYou'll love this job if youAre driven by impact and enjoy working on high-stakes, high-visibility projectsEnjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational membersThrive in cross-functional teams and enjoy building features alongside developers and product teamsQualificationsMinimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related fieldMinimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related fieldDemonstrated expertise building production-grade agentic systems and toolsYou are comfortable writing production quality code (we use Python)Expertise with deep learning frameworks (we use PyTorch)Familiarity in deploying machine learning models at scale in production environmentsExperience in writing technical documentation, mentoring, and presenting to technical audiencesProven track record of owning a system, feature, or component, leading or collaborating with multiple engineers and teamsThe base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $210,000 to $280,000. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits for more details about the Company’s benefit plans/programs. Equal Opportunity at SentrySentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a d ... (truncated, view full listing at source)
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