Palo Alto Principal Engineer Software AI/ML 

United States, California 

273987285

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Impact

• Develop & Optimize LLMs: Lead the design, fine-tuning, and optimization of state-of-the-art LLMs for various cybersecurity applications, focusing on both performance and accuracy.

• Model Evaluation: Conduct in-depth evaluations of LLMs, assessing their effectiveness, efficiency, and business alignment.

• AI Technology Integration: Implement advanced AI technologies, such as Retrieval-Augmented Generation (RAG), function calling, and code interpreters, to enhance LLM capabilities.

• Research & Development: Stay at the forefront of advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural networks.

• Parallel Training Techniques: Utilize data and model parallel training techniques to efficiently manage large-scale models.

• Cross-Functional Leadership: Work closely with ML engineers, data scientists, and product teams to guide, mentor, and foster collaboration across disciplines.

• Documentation & Communication: Maintain detailed documentation of models, methodologies, and findings, ensuring clear communication across the organization.

• Product Strategy: Contribute to the AI-driven product roadmap, vision, and strategic direction.

• New Initiatives & Architecture: Lead the incubation of new initiatives, design scalable AI/ML solutions, and drive strategic technology choices for delivery within a microservices architecture.

• Model Deployment: Design, test, and deploy machine learning models, including LLMs, and develop scalable pipelines for both batch and real-time use cases.

Your Experience

• Bachelor's degree in Computer Science, Engineering, or a related field.

• 8+ years of industry experience in machine learning, data analytics, and software engineering.

• Programming: Expertise in Python (or Go).

• LLM Expertise: Proven experience working with large language models (e.g., open ai, LLAMA, GEMINI.).

• Deep Learning: Strong theoretical or empirical understanding of deep learning techniques and frameworks.

• ML Model Deployment: Experience in building, testing, and deploying machine learning models, particularly large language models.

• Debugging & Analytical Skills: Strong ability to troubleshoot and optimize models.

• Cloud & Distributed Computing: Familiarity with building applications using Google cloud platform(GCP) computing environments.

• MLOps/LLMOps: Experience with DevOps/MLOps practices for machine learning.

• Communication: Excellent communication skills for explaining technical concepts and collaborating with cross-functional teams.

• Passion: A keen interest in staying updated with the latest AI and machine learning trends.

• Preferred Skills & Experience

• Advanced Degree: Master's or PhD in Computer Science, AI, or related fields, with a focus on machine learning and NLP.

• Cybersecurity Experience: Experience working within the cybersecurity domain.

• GenAI Solutions: Familiarity with building GenAI solutions using the RAG framework and LLM Agentic applications.

We define the industry, instead of waiting for directions. We need individuals who feel comfortable in ambiguity, excited by the prospect of a challenge, and empowered by the unknown risks facing our everyday lives that are only enabled by a secure digital environment.

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 $200 - $225/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.