Machine Learning Engineer
: Job Details :

Bad 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. 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 role

As a Machine Learning Engineer on Sentry's AI/ML team, you'll be directly responsible for developing the models and algorithms used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating machine learning into our core products, from error classification 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

• Solve hard problems in the fields of time-series analysis and NLP
• Work directly with Sentry's novel (and massive) dataset of errors, spans, and profiles
• Own the development of major initiatives

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 2+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field
• Minimum 4+ years of professional experience with Bachelor's degree in computer science, machine learning, or a related field
• You are comfortable writing production quality code (we use Python)
• Expertise with deep learning frameworks (we use PyTorch)
• Expertise applying statistical techniques and algorithms to time-series data
• Familiarity with OLAP databases, ideally in the context of time-series data
• Familiarity in deploying machine learning models at scale in production environments
• Experience in writing technical documentation, mentoring, and presenting to technical audiences
• Proven track record of owning a system, feature, or component, leading or collaborating with multiple engineers and teams

The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $160,000 to $175,000. 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 Sentry

Sentry 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 diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible.

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