Senior Staff Machine Learning Engineer

### Who you are
- MS or Ph.D. in Computer Science or a related field, with a focus on Machine Learning, and 4+ years of industry experience delivering ML systems in production environments
- Strong problem solver with collaborative team player with clear communication skills, able to work effectively across engineering, product, and SRE teams
- Solid foundation in Machine Learning, Deep Learning, and NLP, with hands-on experience using modern architectures such as transformer-based models and representation learning techniques
- Practical experience applying Large Language Models (LLMs) to real-world problems, including text understanding, classification, extraction, summarization, or reasoning over large-scale and noisy data
- Experience designing, implementing, and operating LLM-powered components in production, including prompt design, model adaptation or fine-tuning, evaluation, and cost/performance optimization
- Experience with MLOps / AIOps practices for operating ML and LLM systems in production, including model lifecycle management, monitoring, logging, alerting, retraining workflows, and debugging production issues
- Understanding of model quality, robustness, and safety considerations, including evaluation methodologies, failure modes, and guardrails required for production ML systems in security-sensitive environments
- Strong experience with ML frameworks, libraries, and tooling (e.g., PyTorch, Tensorflow, Keras, Scikit-learn, Kubeflow), and solid software engineering fundamentals
- Ability to independently own ML features end-to-end, from problem formulation and system design to implementation, deployment, and iterative improvement in production
- Proficient in Python, working knowledge of Java, Linux, and shell scripting
- Experience building and operating services on cloud platforms (GCP and/or AWS) and in containerized environments (Docker, Kubernetes)
- Familiarity with AI agent–based approaches, such as multi-step inference pipelines, tool-augmented LLM workflows, or systems that combine models, heuristics, and external signals to drive reliable decisions
- Experience with website content understanding, website classifications, security, or large-scale internet data is a strong plus
- Familiarity with relational and NoSQL data stores such as MySQL, MongoDB, or similar systems
- Experience applying LLMs and agentic systems in security-sensitive or high-precision domains is a strong plus

### What the job involves
- Design, build, and operate production machine learning systems that balance model quality, cost, latency, and reliability in a security-sensitive environment
- Own the end-to-end lifecycle of ML and LLM components, from problem formulation and model development to production deployment, monitoring, and iterative improvement
- Integrate ML and LLM-based services with backend systems and data pipelines, ensuring scalability, observability, and safe operation in production
- Develop and maintain automated training, evaluation, and retraining pipelines, and build data analysis tools to continuously improve model performance as data and threats evolve
- Partner closely with Product Managers and domain experts to translate product and security requirements into robust ML solutions with clear success metrics
- Collaborate with software engineers and SREs on release planning, deployment strategies, monitoring, and incident response to ensure reliable and predictable production behavior

### Benefits
- Healthcare: We value your health and provide options so you can choose what best supports your lifestyle and personal health goals. Various nationwide plans — including Blue Shield of California, Kaiser Permanente, Delta Dental, VSP, and more — are available to you and your family. Our providers offer the flexibility you want and the coverage you need
- Wellness: With a large on-site gym and daily, instructor-led exercise classes at HQ in Santa Clara, Palo Alto Networks actively supports employee fitness. Our juice bar, Gym & Juice, features fresh juice blends, a quick and nutritious option pre- or post-workout. And our ongoing wellness speaker series highlights the latest trends in health and wellness
- Development: Professional development is serious business at Palo Alto Networks, where the Talent Development team offers 25+ courses to help employees boost their careers and develop leadership capability
- Financial: Most roles are eligible for equity grants, and we now offer new hires a quarterly vesting schedule right away. We want you to be fairly compensated and rewarded as soon as you make an impact – on our team, that happens immediately! And because we consider every employee a stakeholder in our long-term success, we offer an Employee Stock Purchase Plan (ESPP) with a 24-month lookback. From life insurance to health savings accounts, we provide ways to help you protect and grow your wealth. Palo Alto Networks offers both traditional and Roth 401(k) options, along with a company match of 50% to a max annual amount of $1,000
- Time Off: In addition to paid corporate holidays, Flexible Time Off programs empower our employees to balance their work schedules with personal time off. We offer 12 weeks of full pay for medical leave and 6 weeks of full pay for parental leave. As a company with strong ties to the military and veterans, we also offer 26 weeks of full pay for military leave
- Perks: Our corporate discount program provides employees with significant discounts on merchandise, travel and entertainment. We offer many on-site perks at headquarters, including cafeterias, fuel service, dry cleaning service, EV charging stations, and a company store. We also provide complimentary drinks, fresh fruit, and snacks in break rooms across our campus to help everyone power through the day.

Life at Palo Alto Network