Principal Machine Learning Engineer (SQL - RAG Systems)
Expanse
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 highly skilled Principal Machine Learning Engineer with expertise in advanced ML techniques, data analytics, and the design and deployment of high-performance Retrieval-Augmented Generation (RAG) systems. This role is ideal for someone passionate about leveraging machine learning to solve complex problems at scale.
Your Impact
- Design and implement cutting-edge machine learning models for RAG systems with a focus on scalability and real-world application performance
- Develop algorithms to optimize retrieval, inference, and response quality, including reranking techniques
- Collaborate on projects involving NLP, Recommender Systems, and large language models (LLMs)
- Work with open-source agent frameworks like LangChain, LLamaIndex or Langgraph for advanced AI solutions
- Design and manage scalable database solutions (SQL, OLAP, OTAP) to support high-performance analytics
- Fine-tune ML models and implement formal methods toolchains when necessary
- Communicate effectively across teams, influencing stakeholders at all organizational levels
Qualifications
Your Experience
- 8+ years of industry experience in machine learning, data analytics, and software engineering
- Strong expertise in Python, PyTorch, TensorFlow, and foundational computer science concepts (algorithms, data structures, system design)
- Familiarity with vector search technologies and frameworks in RAG systems
- Proficiency with SQL databases and experience handling performance, scalability, and optimization challenges
- M.S. or Ph.D. in Computer Science, Mathematics, Electrical Engineering, or a related field (or equivalent military experience)
Preferred
- Proven experience designing and deploying RAG systems for real-world use cases
- In-depth understanding of retrieval optimization, reranking algorithms, and model fine-tuning techniques
- Strong background in NLP, recommender systems, and working with LLMs
- Excellent teamwork and communication skills with the ability to work effectively as both a self-driven individual contributor and team player
Additional Information
The Team
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 $151000 - $246500/ YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
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.
Is role eligible for Immigration Sponsorship?: Yes
