Principal Machine Learning Engineer (RAG Pipeline Optimization)

$151,000 - $210,500/Yr

Palo Alto Networks - Santa Clara, CA

Full-time - Principal

Santa Clara, CA

Professional, Scientific, and Technical Services

About the position

The Principal Machine Learning Engineer will focus on optimizing RAG (Retrieval-Augmented Generation) pipelines to enhance cybersecurity solutions. This role involves leveraging advanced machine learning techniques to analyze vast amounts of data, contributing to the development of innovative AI and machine learning solutions that protect devices and discover threats. The position emphasizes collaboration, ongoing learning, and the creation of impactful security features for a widely used security platform.

Responsibilities

• Design and develop workflow frameworks using formal methods and algorithms, including result collection and visualization tools.
• Create and deliver training materials for team members and stakeholders.
• Engage actively with the security community through collaborations and contributions to industry technology evolution.
• Work in a fast-paced team to create and deliver new product and mission features to the security platform.
• Leverage advanced machine learning techniques on large datasets to solve network security challenges.

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, with a 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 and response quality.
• 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.

Nice-to-haves

• Experience with designing and deploying high-performance RAG systems for real-world applications.
• In-depth knowledge of reranking algorithms and experience in fine-tuning models to optimize retrieval performance and response quality.
• 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 selected by employees.
• Mental and financial health resources.
• Personalized learning opportunities.