Principal Machine Learning Engineer (RAG Pipeline Optimiation)

$151,000 - $225,000/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 at Palo Alto Networks will focus on optimizing the RAG (Retrieval-Augmented Generation) pipeline, leveraging advanced machine learning techniques to enhance network security solutions. This role involves designing and developing workflow frameworks, engaging with the security community, and contributing to the evolution of industry technology in cybersecurity. The position is based in Santa Clara, California, and emphasizes collaboration and innovation in a fast-paced environment.

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 required.
• 8+ years of industry experience in Machine Learning techniques and data analytics.
• 8+ years of experience in design, algorithms, and data structures.
• Expertise with one or more programming languages such as Java, Python, or Rust.
• Experience with 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.).
• 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 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.