Principal Machine Learning Engineer (RAG Pipeline Optimization)

$151,000 - $225,000/Yr

Palo Alto Networks - Santa Clara, CA

Full-time - Senior

Santa Clara, CA

Professional, Scientific, and Technical Services

About the position

The Principal Machine Learning Engineer at Palo Alto Networks will focus on optimizing RAG (Retrieval-Augmented Generation) pipelines to enhance network security solutions. This role involves leveraging advanced machine learning techniques to analyze vast amounts of data, contributing to the development of AI-driven products that protect devices and provide intelligence against threats. The position emphasizes collaboration, innovation, and the delivery of impactful security features to a wide customer base.

Responsibilities

• Create and deliver new product and mission features to the security platform.
• Engage and contribute to the security community through collaborations.
• Design and develop workflow frameworks using formal methods and algorithms.
• Collect results and visualize data through monitoring tools.
• Create and deliver training materials.

Requirements

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

Nice-to-haves

• Experience with NLP, Recommender Systems, and LLM.
• Experience with Formal Methods toolchain (z3, cvc5, TLA+).

Benefits

• FLEXBenefits wellbeing spending account with over 1,000 eligible items.
• Mental and financial health resources.
• Personalized learning opportunities.