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Principal Machine Learning Engineer (SQL - RAG Systems)

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

Average salary estimate

$198750 / YEARLY (est.)
min
max
$151000K
$246500K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Principal Machine Learning Engineer (SQL - RAG Systems), Palo Alto Networks

Palo Alto Networks is on the lookout for a Principal Machine Learning Engineer specializing in SQL and Retrieval-Augmented Generation (RAG) systems to join our team in Santa Clara, CA. In this role, you will harness your extensive experience in machine learning and data analytics to craft innovative solutions that truly make an impact in the cybersecurity field. You will be at the forefront of developing and implementing cutting-edge ML models with a focus on real-world applications, optimizing algorithms for retrieval and response quality, and collaborating on projects that leverage Natural Language Processing and large language models. Your expertise in SQL databases will come into play as you design scalable solutions to support high-performance analytics. You'll have the opportunity to work with exciting open-source frameworks like LangChain, utilizing the latest technologies to influence and collaborate with teams across the organization. If you enjoy tackling complex challenges with a team of passionate innovators, this is the place for you. At Palo Alto Networks, we are dedicated to fostering a supportive environment where unique ideas flourish, empowering every individual to contribute to shaping the future of cybersecurity. Come and be part of our dynamic team, working at the intersection of technology and security where every day presents a new opportunity to protect our digital way of life.

Frequently Asked Questions (FAQs) for Principal Machine Learning Engineer (SQL - RAG Systems) Role at Palo Alto Networks
What are the responsibilities of a Principal Machine Learning Engineer at Palo Alto Networks?

As a Principal Machine Learning Engineer at Palo Alto Networks, your responsibilities will include designing and implementing machine learning models for RAG systems, optimizing algorithms for retrieval and response quality, and collaborating on projects involving NLP and large language models. You'll also manage scalable database solutions and effectively communicate with stakeholders across various teams.

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What qualifications are needed to apply for the Principal Machine Learning Engineer position at Palo Alto Networks?

To qualify for the Principal Machine Learning Engineer position at Palo Alto Networks, you should have over 8 years of industry experience in machine learning, data analytics, and software engineering. A strong background in Python, TensorFlow, and SQL databases is essential, along with a master's or Ph.D. in Computer Science or a related field. Familiarity with RAG systems and vector search technologies is preferred.

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What kind of projects will the Principal Machine Learning Engineer work on at Palo Alto Networks?

The Principal Machine Learning Engineer at Palo Alto Networks will work on high-impact projects focusing on developing cutting-edge machine learning models. These include optimizing retrieval algorithms, fine-tuning ML models, and engaging in collaborative efforts around NLP and recommender systems. You will tackle complex cybersecurity challenges using innovative technology.</>

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Is the Principal Machine Learning Engineer role eligible for immigration sponsorship at Palo Alto Networks?

Yes, the Principal Machine Learning Engineer position at Palo Alto Networks is eligible for immigration sponsorship, ensuring that talented individuals from diverse backgrounds can join our innovative team.

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What is the work environment like for the Principal Machine Learning Engineer at Palo Alto Networks?

The work environment for the Principal Machine Learning Engineer at Palo Alto Networks emphasizes collaboration, problem-solving, and a commitment to innovation. You will work closely with a talented team in a dynamic atmosphere, with the flexibility offered where needed to foster creativity and collaboration.

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Common Interview Questions for Principal Machine Learning Engineer (SQL - RAG Systems)
Can you describe a challenging machine learning project you've worked on?

When answering this question, provide specifics on the project scope, your role, and the technologies you utilized. Highlight the challenges you faced, how you overcame them, and the impact your work had. This showcases your problem-solving skills and your ability to handle complex projects.

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How do you approach designing an ML model for RAG systems?

Detail your approach starting from understanding the problem domain and data requirements. Discuss the importance of selecting the right algorithms, optimizing for scalability, and integrating with SQL databases. Emphasize your process of fine-tuning models and validation techniques to ensure performance.

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What machine learning frameworks are you most comfortable with?

Discuss your hands-on experience with frameworks like TensorFlow and PyTorch. Mention specific projects where you successfully utilized them and elaborate on your familiarity with related libraries and tools relevant to RAG systems.

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How do you stay updated on the latest advancements in machine learning?

Mention the resources you use to keep abreast of developments, such as academic journals, online courses, workshops, or participation in ML communities. Highlight how this continuous learning helps you apply the latest techniques to your work.

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Can you explain retrieval optimization and its significance in RAG systems?

Provide an overview of retrieval optimization techniques, such as reranking algorithms, and explain their importance in enhancing model performance in RAG systems. Discuss how effective retrieval impacts the overall success of the model in real-world applications.

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What strategies do you use to communicate complex technical concepts to stakeholders?

Emphasize the importance of tailoring your communication style to your audience. Discuss using visual aids, analogies, or simplified explanations to make complex concepts accessible. Mention any experiences where you successfully influenced team decisions.

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Tell me about a time you had to collaborate with a cross-functional team.

Share a specific example where you worked with teams from different disciplines—such as software engineering, product management, or data science. Highlight your role, the challenges faced, and the successful outcomes achieved through collaboration.

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What are some common pitfalls in machine learning projects and how do you avoid them?

Discuss awareness of issues like overfitting, data bias, and improper feature selection. Explain how you proactively address these pitfalls during the design and implementation phases, ensuring rigorous testing and validation practices.

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How do you handle incomplete or messy data when building machine learning models?

Share your strategies for data preprocessing and cleaning, emphasizing your approach to ensuring the quality of the data that feeds into your models. Discuss techniques for dealing with missing values and noise in the dataset.

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Why do you want to work at Palo Alto Networks?

Reflect on the company's mission and values, particularly how they align with your personal drive for innovation in cybersecurity. Discuss what excites you about the role and how you see yourself contributing to their goals.

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Being the cybersecurity partner of choice, protecting our digital way of life.

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DATE POSTED
December 1, 2024

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