Sr Manager Machine Learning (Aiops)

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.

FLEXWORK is an employee-centric reimagining of how we work. We built FLEXWORK based on employee feedback – it is about flexibility, trust, and choice whenever possible. It’s been a journey of disruption that has yielded the best of our values. We offer as much flexibility as possible, and choices that enable you to be most productive, including benefits that meet your needs and learning opportunities that you feel passionate about.

Your Career

You will be able to build a career applying Machine Learning and AI to different challenges around Firewalls and Network Security Operations in general.

From Timeseries techniques like Anomaly Detection and forecasting, passing through Causality techniques for Root Cause Analysis, all the way to recent advances like Generative AI, you will never be out of exciting challenges.

You will help to create AI solutions on top of one of the biggest data lakes with exabytes of data and hundreds of thousands of devices constantly sending telemetry.

At Palo Alto Networks, Sr. Managers of Engineering are:

• Leaders who can communicate effectively and succinctly with hands-on engineers as well as executives.
• Role models and mentors who lead by example and are willing to be hands-on when the team or the business needs it.
• Experts that have not only the technical experience to take on and provide technical leadership to major projects but also manage a team of engineers and data scientists.
• Committed professionals who deliver on critical business needs and are recognized across the organization as go-to engineering resources on given domains.

We expect office-based employees to be in the office four days per week, with one day working from where they choose. We believe being together facilitates casual conversations and those magic moments where we can work on issues and ideas informally. These moments build capability and deepen trusted relationships and allow our people to feel safe in taking risks and being disruptive. Like so many companies, we are working through the details and things could change …. but in general if a role is deemed office-based we want our teams to be together four days per week.

Your Impact

• You will work in a fast-paced team to create and deliver new features in a speedboat product that many customers use daily to ensure their network operation is healthy and secure
• You will be part of a team using ML and AI to redefine the way Network Security operations are done
• You will help to design and develop AI/ML frameworks that allow us to apply algorithms at the scale of hundreds of thousands of devices reporting thousand of metrics in per minute bases
• You will collaborate in the design of user experiences that allow users to consume deep and complex insights in an easy and manageable way

Qualifications

Your Experience

• Proven leadership skills with an ability to deliver under tight deadlines
• Proven capacity to go beyond ML algorithms and models by contributing in the design and implementation of services and pipelines that expose ML artifacts
• M.S. or Ph.D degree in Computer Science, Mathematics, Statistics or related field or equivalent military experience required
• Thorough understanding of ML Ops best practices like algorithms/models monitoring and orchestration - Experience working with Google Vertex AI platform will be a plus
• Experience with deep learning frameworks such as PyTorch and TensorFlow, Huggingface Transformers, or related is a big plus
• Proven ability to collaborate with many cross-functional teams with an emphasis on end-to-end delivery
• 8+ experience in design, algorithms, and data structures - Expertise with one or more of the following languages is a must - Java, Python
• Capacity to become a self-driven individual contributor and an excellent team player when the teams and the business requires it
• 10+ years of industry experience in Machine Learning techniques and data analysis - Experience with Timeseries, Causality, and NLP (specially LLM) is a big plus

Additional Information

The Team

We are on a mission to build the industry's best AIOps product that enables our customers to keep their network healthy and secure thanks to AI and ML.

Our engineering team is at the core of the application of AI at a large scale – challenging how we, and the industry, think about security network operations.

We are constantly chasing the next big challenge to produce the most significant value for our customers. And that's why we need individuals who feel comfortable in ambiguity and are willing to be creative to find the best balance between innovation and speed.

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 [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.

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 $187,000/yr to $302,500/yr. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here .

#LI-TD1