Sr. Machine Learning Engineer
Role details
Job location
Tech stack
Job description
As a Machine Learning Engineer on our Internet Security Research Team, you will be a key innovator transforming ideas into products for our next-generation security platform. You will work with data scientists and security researchers to implement projects that detect and defend against emerging web security threats. This role is part of our dedicated 2026 New Hire cohort, with an anticipated start date in August 2026.
Key Responsibilities Perform in-depth data analysis to deeply understand security data and the threat domain.
Design, train, and evaluate machine learning algorithms to significantly improve the analytical performance of threat detection models.
Build and productionize machine learning models and develop the distributed systems that utilize them to analyze and categorize enormous volumes of URLs.
Design and build robust, scalable machine learning systems, carefully balancing cost with model performance.
Establish automated training pipelines and develop data analytics tools to incrementally enhance model performance on a growing dataset.
Proactively collaborate with data scientists, security researchers, and Product Managers to gather requirements, design, and implement systems.
Challenge existing approaches curiously and positively to simplify complex systems and improve efficiency.
Work effectively with other engineers and SREs on release, deployment, and operational processes, ensuring alignment and accountability., Neep Help? Have questions or want to provide feedback? Please fill out this form and we will get in touch with you as soon as possible. Thanks! Subject Your Email Message Captcha
Requirements
MS or PhD in Machine Learning, Computer Science, Data Science, or a related field, with graduation expected between December 2025 and July 2026.
Proficiency in at least one programming language such as Python, Java, or Golang.
Experience applying supervised and/or unsupervised machine learning algorithms on various data types.
Preferred Qualifications
Working knowledge of Natural Language Processing (NLP) techniques or document classification.
Familiarity with advanced machine learning architectures like transformers and convolutional networks.
Experience with cloud platforms (Google Cloud Platform, AWS) and container-based development (Docker, Kubernetes).
Ability to design, implement, and deploy system components, including regression and integration testing.
Benefits & conditions
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
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Our Commitment
We're trailblazers that dream big, take risks, and challenge cybersecurity's status quo. It's simple: we can't accomplish our mission without diverse teams innovating, together.