You have a comprehensive understanding of containerization (Docker, Kubernetes), high-throughput data pipelines, and proactive system monitoring. Exceptional ability to run end-to-end research-to-production initiatives, showcasing an analytical mindset capable of translating raw data into highly accurate, real-time defensive actions. Extensive, hands-on experience utilizing, fine-tuning, and optimizing open-source generative AI frameworks and libraries (e.g., Hugging Face, PyTorch, vLLM, DeepSpeed) to build and deploy high-performance models. Proven experience architecting data solutions and working within major cloud and big data ecosystems (e.g., GCP, AWS, Snowflake) to ingest, process, and analyze high-velocity, petabyte-scale datasets. Outstanding communication and presentation skills, with a demonstrated ability to align cross-functional engineering, product, and research teams toward unified technical goals. Preferred Qualifications MSc/PhD in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. Background in the cybersecurity domain Our Commitment We’re trailblazers that dream big, 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 accommodations@paloaltonetworks.com. 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, protecte
