Senior ML Engineer (Internet Security)

Your Career

You will build machine learning models and develop big data and distributed systems that use the models to analyze and categorize an enormous amount of URLs. You will be a key person in transforming ideas into products which are part of the next generation security platform. The Internet Security Research Team is responsible for innovating new security techniques.

Your Impact

• Design build and operate production machine learning systems that balance model quality cost latency and reliability in a security-sensitive environment.

• Own the end-to-end lifecycle of ML and LLM components from problem formulation and model development to production deployment monitoring and iterative improvement.

• Integrate ML and LLM-based services with backend systems and data pipelines ensuring scalability observability and safe operation in production.

• Develop and maintain automated training evaluation and retraining pipelines and build data analysis tools to continuously improve model performance as data and threats evolve.

• Partner closely with Product Managers and domain experts to translate product and security requirements into robust ML solutions with clear success metrics.

• Collaborate with software engineers and SREs on release planning deployment strategies monitoring and incident response to ensure reliable and predictable production behavior.

Qualifications :

Your Experience 

• Strong problem solver with collaborative team player with clear communication skills able to work effectively across engineering product and SRE teams.

• Solid foundation in Machine Learning Deep Learning and NLP with hands-on experience using modern architectures such as transformer-based models and representation learning techniques.

• Practical experience applying Large Language Models (LLMs) to real-world problems including text understanding classification extraction summarization or reasoning over large-scale and noisy data.

• Experience designing implementing and operating LLM-powered components in production including prompt design model adaptation or fine-tuning evaluation and cost/performance optimization.

• Familiarity with AI agentbased approaches such as multi-step inference pipelines tool-augmented LLM workflows or systems that combine models heuristics and external signals to drive reliable decisions.

• Experience with MLOps / AIOps practices for operating ML and LLM systems in production including model lifecycle management monitoring logging alerting retraining workflows and debugging production issues.

• Understanding of model quality robustness and safety considerations including evaluation methodologies failure modes and guardrails required for production ML systems in security-sensitive environments.

• Strong experience with ML frameworks libraries and tooling (e.g. PyTorch Tensorflow Keras Scikit-learn Kubeflow) and solid software engineering fundamentals.

• Ability to independently own ML features end-to-end from problem formulation and system design to implementation deployment and iterative improvement in production.

• Experience with website content understanding website classifications security or large-scale internet data is a strong plus.

• Proficient in Python working knowledge of Java Linux and shell scripting.

• Experience building and operating services on cloud platforms (GCP and/or AWS) and in containerized environments (Docker Kubernetes).

• Familiarity with relational and NoSQL data stores such as MySQL MongoDB or similar systems.

• Experience applying LLMs and agentic systems in security-sensitive or high-precision domains is a strong plus.

• MS or Ph.D. in Computer Science or a related field with a focus on Machine Learning and 2 years of industry experience delivering ML systems in production environments.

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Additional Information :

The Team

As a member of the Internet Security Research Team specifically Advanced URL Filtering Data Science you will work closely with data scientists security researchers and other engineers on implementing different projects to detect and defend against various emerging threats in the areas of Web Security.

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/commissioned roles) is expected to be between $205000 - $235000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

Our Commitment

Were problem solvers that take risks and challenge cybersecuritys status quo. Its simple: we cant 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  .

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.

Remote Work :

No

Employment Type :

Full-time