Staff Engineer Software (AI Customer Co-pilot)

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 Staff AI Engineer to join our growing team and contribute to the development and optimization of cutting-edge AI technologies, including Large Language Models (LLMs). In this role, you will work closely with technical teams to develop impactful AI-driven solutions that enhance our cybersecurity capabilities. This is a great opportunity for an experienced engineer to grow in an innovative environment and make significant contributions to the field of AI in cybersecurity.

Your Impact

• Develop & Optimize AI Models: Contribute to the design, fine-tuning, and optimization of AI models, including large language models (LLMs), for use in cybersecurity applications.

• Model Evaluation: Participate in the evaluation of model performance, ensuring models meet business requirements and performance standards.

• AI Technology Integration: Assist in integrating advanced AI technologies like Retrieval-Augmented Generation (RAG), function calling, and code interpreters into our existing systems.

• Research & Learning: Keep up to date with the latest advancements in AI and machine learning to incorporate best practices into product development.

• Model Training: Work with data and model parallel training techniques to efficiently manage large-scale models.

• Collaboration: Collaborate with ML engineers, data scientists, and product teams to ensure seamless integration of AI technologies and alignment with product goals.

• Documentation & Communication: Contribute to documenting AI models and methodologies, and communicate technical findings clearly to both technical and non-technical stakeholders.

• AI Solutions Delivery: Assist in the design, testing, and deployment of scalable machine learning models and pipelines for batch and real-time applications.

Qualifications

Your Experience 

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

• Experience: 1+ years of hands-on experience in AI, machine learning, or data science.

• Programming: Proficiency in Python (or Go).

• AI Model Experience: Experience working with large language models (e.g., Open AI, LLAMA, GEMINI) or similar AI technologies.

• Deep Learning: Familiarity with deep learning techniques and frameworks.

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

• Cloud & Distributed Computing: Familiarity with cloud-based infrastructure Google Cloud Platform (GCP)

• MLOps: Experience with DevOps/MLOps practices for machine learning development and deployment.

• Problem Solving: Strong analytical and troubleshooting skills for AI model optimization.

• Communication: Effective communication skil