Job description

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who Are We This role is remote, but distance is no barrier to impact. Our hybrid teams collaborate across geographies to solve big problems, stay close to our customers, and grow together. You will be part of a culture that values trust, accountability, and shared success where your work truly matters. Job Description Job Summary 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. Qualifications (Additional Job Description) Required Qualifications 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 (GCP, AWS) and container-based development (Docker, Kubernetes). Ability to design, implement, and deploy system components, including regression and integration testing. Compensation Disclosure 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. - /yr 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. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations paloaltonetworks.com . Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Requirements

Must-haves

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.
Qualifications (Additional Job Description)
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.

Nice-to-haves

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 (GCP, AWS) and container-based development (Docker, Kubernetes).
Ability to design, implement, and deploy system components, including regression and integration testing.
Compensation Disclosure
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.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonjavagolanggcpawsdockerkubernetes

Platform: workday
Effort: long