Senior Machine Learning Engineer
The posting does not state a salary. This range is our estimate from the role, the location and the stack — treat it as a guide, not an offer.
- Level
- Senior
- Apply from
- Apply from anywhere
About the role
- Transform ideas into products for security
- Collaborate with data scientists and researchers
- Design and evaluate machine learning algorithms
- Build scalable machine learning systems
- Establish automated training pipelines
Skills the posting asks for
- Python
- Java
- Golang
- NLP
- AWS
Summarised from the employer’s posting, which is reproduced in full below.
The employer’s full posting
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 ,
- (Desirable) Working knowledge of Natural Language Processing (NLP) techniques or document classification ,
- (Desirable) Familiarity with advanced machine learning architectures like transformers and convolutional networks ,
- (Desirable) Experience with cloud platforms (GCP, AWS) and container-based development (Docker, Kubernetes) ,
- (Desirable) Ability to design, implement, and deploy system components, including regression and integration testing
- 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 ,
- 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