Machine Learning Engineer

$160,000 - $175,000/Yr

Sentry - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

51-100 employees

Insurance Carriers and Related Activities

About the position

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 natural language processing (NLP). You will work directly with Sentry's novel (and massive) dataset of errors, spans, and profiles, and own the development of major initiatives. This position offers the opportunity to join the AI/ML team as one of its foundational members, allowing you to thrive in cross-functional teams and enjoy building features alongside developers and product teams.

Responsibilities

• Develop models and algorithms to enhance product capabilities.
• Integrate machine learning into core products, focusing on error classification and predictive analytics.
• Solve complex problems in time-series analysis and NLP.
• Work with large datasets of errors, spans, and profiles.
• Own the development of major initiatives within the AI/ML team.

Requirements

• 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 a Bachelor's degree in computer science, machine learning, or a related field.
• Comfortable writing production quality code, primarily in Python.
• Expertise with deep learning frameworks, specifically PyTorch.
• Experience applying statistical techniques and algorithms to time-series data.
• Familiarity with OLAP databases, ideally in the context of time-series data.
• Experience deploying machine learning models at scale in production environments.
• Proficient in writing technical documentation and mentoring others.
• Proven track record of owning a system, feature, or component, and collaborating with multiple engineers and teams.

Benefits

• Incentive compensation
• Equity grants
• Paid time off
• Group health insurance coverage