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Palo Alto Networks

Sr Machine Learning Engineer (GenAI/LLM)

Sorry, this job was removed at 01:12 p.m. (PST) on Thursday, Aug 07, 2025
In-Office
Santa Clara, CA, USA
120K-200K Annually
In-Office
Santa Clara, CA, USA
120K-200K Annually

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Company Description

Our Mission

At Palo Alto Networks® everything starts and ends with our mission:

Being the cybersecurity partner of choice, protecting our digital way of life.
Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.

Who We Are

We take our mission of protecting the digital way of life seriously. We are relentless in protecting our customers and we believe that the unique ideas of every member of our team contributes to our collective success. Our values were crowdsourced by employees and are brought to life through each of us everyday - from disruptive innovation and collaboration, to execution. From showing up for each other with integrity to creating an environment where we all feel included.

As a member of our team, you will be shaping the future of cybersecurity. We work fast, value ongoing learning, and we respect each employee as a unique individual. Knowing we all have different needs, our development and personal wellbeing programs are designed to give you choice in how you are supported. This includes our FLEXBenefits wellbeing spending account with over 1,000 eligible items selected by employees, our mental and financial health resources, and our personalized learning opportunities - just to name a few!

At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work full time from our office with flexibility offered where needed. This setup fosters casual conversations, problem-solving, and trusted relationships. Our goal is to create an environment where we all win with precision.

Job Description

Your Career

We are seeking a Sr LLM Application Engineer to join our team and lead the development and optimization of cutting-edge Large Language Models (LLMs) within the cybersecurity domain. You will play a pivotal role in advancing our AI technology, leveraging Generative AI, LLMs, and ML Ops to drive impactful solutions. As a technical leader, you will lead high-impact projects, mentor cross-functional teams, and contribute to the strategic direction of our AI-driven cybersecurity initiatives.

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.

Qualifications

Your Experience 

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

  • Experience: 5+ 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

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

Additional Information

The Team

We are on a mission to build the industry's best Security large language model.

Our engineering team is at the core of our products – connected directly to the mission of preventing cyberattacks. We are constantly innovating – challenging the way we, and the industry, think about cybersecurity. Our engineers don’t shy away from building products to solve problems no one has pursued before.

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 $120,000 - $200,000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

#LI-TD1

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.

HQ

Palo Alto Networks Santa Clara, California, USA Office

Designed to build connections, provide transparency and support productive work, the campus fosters community and conversation through cafes, amenities and other social hubs, keeping Palo Alto Networks unique culture thriving as it continues to grow and scale.

Palo Alto Networks San Francisco, California, USA Office

San Francisco, United States

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Key Facts About San Francisco Tech

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  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

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