Principal Machine Learning Engineer (RAG Pipeline Optimization)

Your Career

You will be able to build a career solving network security challenges by leveraging advanced machine learning techniques on exabytes of data. You will help create and deliver the most advanced AI and Machine Learning solutions to discover threats, provide intelligence, and protect devices.

Your Impact

• You will work in a fast-paced team to create and deliver new product and mission features to the security platform that many customers use daily
• You will actively engage and contribute to the security community through collaborations
• You will be part of the team that is leading and driving industry technology evolution in security and creating a positive impact on business
• Design and development of workflow frameworks (using formal methods and algorithms), with result collection and visualization, monitoring tools
• Creation and delivery of training materials

Your Experience 

• 8+ years of industry experience in Machine Learning techniques and data analytics
• 8+ experience in design, algorithms, and data structures - Expertise with one or more of the following languages is a must - Java, Python, Rust
• M.S. or Ph.D degree in Computer Science, Mathematics, Electrical Engineering, or a related field or equivalent military experience required
• Experience with designing and deploying high-performance RAG systems for real-world applications, with a strong understanding of scaling retrieval and inference challenges is strongly preferred
• In-depth knowledge of reranking algorithms (RRF, BM25, DPR, etc.) and experience in fine-tuning models to optimize retrieval performance and response quality will be a plus
• Experience with NLP, Recommender Systems, and LLM is strongly preferred
• Experience with Formal Methods toolchain (z3, cvc5, TLA+)  will be a plus
• Excellent communication skills with the ability to influence at all levels of the organization
• A self-driven individual contributor and an excellent team player

The Team

Drawing on the near real-time data collected through PAN-OS device telemetry, our industry-leading next-generation insights product (AIOps for NGFW) gives large cybersecurity operators a force multiplier that provides visibility into the health of their next-generation-firewall (NGFW) devices. It enables early detection of issues at various levels of the stack via advanced time-series forecasting and anomaly detection using novel deep-learning techniques. Our mission is to leverage advanced AI and machine learning technologies to build intelligent solutions that empower support engineers to solve customer cases more efficiently. By creating AI-driven pipelines, we streamline the troubleshooting process, providing faster, more accurate insights from complex data patterns. Our team thrives on innovation, collaboration, and a passion for using data science to drive real-world impact, helping organizations stay secure in an ever-evolving digital landscape. Join us to shape the future of cybersecurity support with AI-powered solutions.

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 $151000 - $210500/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

We’re problem solvers that 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  [email protected].

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.