Palo Alto Networks
Sr Machine Learning Engineer (GenAI/LLM)
Palo Alto Networks, Santa Clara, California, us, 95053
Overview
Senior Technical Recruiter at Palo Alto Networks 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. Responsibilities
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
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., OpenAI, 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). 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 with RAG framework and LLM Agentic applications. Additional Information
Our 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 and focuses on cybersecurity innovation. We value ambiguity, challenge, and empowerment in solving problems that advance secure digital environments. 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 is expected to be between $120,000 - $200,000 per year, with potential bonuses and restricted stock units. A description of our employee benefits may be found here. Our Commitment
We are an equal opportunity employer and celebrate diversity in our workplace. We provide reasonable accommodations for qualified individuals with disabilities. If you require assistance, contact accommodations@paloaltonetworks.com. All information will be kept confidential according to EEO guidelines. 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, or other legally protected characteristics.
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Senior Technical Recruiter at Palo Alto Networks 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. Responsibilities
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
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., OpenAI, 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). 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 with RAG framework and LLM Agentic applications. Additional Information
Our 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 and focuses on cybersecurity innovation. We value ambiguity, challenge, and empowerment in solving problems that advance secure digital environments. 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 is expected to be between $120,000 - $200,000 per year, with potential bonuses and restricted stock units. A description of our employee benefits may be found here. Our Commitment
We are an equal opportunity employer and celebrate diversity in our workplace. We provide reasonable accommodations for qualified individuals with disabilities. If you require assistance, contact accommodations@paloaltonetworks.com. All information will be kept confidential according to EEO guidelines. 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, or other legally protected characteristics.
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