Sr. Manager, ML Engineering (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.

Our Approach to Work

We lead with flexibility and choice in all of our people programs. We have disrupted the traditional view that all employees have the same needs and wants. We offer personalization and offer our employees the opportunity to choose what works best for them as often as possible - from your wellbeing support to your growth and development, and beyond!

At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work from the office three days per week, leaving two days for choice and flexibility to work where you feel most effective. This setup fosters casual conversations, problem-solving, and trusted relationships. While details may evolve, our goal is to create an environment where innovation thrives, with office-based teams coming together three days a week to collaborate and thrive, together!

Job Description

Your Career

You will be able to build a career combining Software Engineering and Machine Learning to tackle different challenges around Firewalls and Network Security Operations in general. 

Exciting challenges will be the norm: On the Software Engineering side, you will have the opportunity to build pipelines and analytics features that deal with petabytes of data. While in the Machine Learning side, you will have contact with techniques ranging from Time-series, Anomaly Detection and forecasting, passing through Causality techniques for Root Cause Analysis, all the way to recent advances like Generative AI.

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. Manager of Engineering are:

• 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.
• Role models and mentors who lead by example and are willing to be hands-on when the team or the business needs it.
• Leaders who can communicate effectively and succinctly with hands-on engineers as well as executives.

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 data analytics and ML to redefine the way Network Security operations are done.
• You will help to design and develop Analytics and 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

• M.S. or Ph.D degree in Computer Science, Mathematics, Statistics or related field.
• 10+ years of industry experience in Big Data, Data Analysis, and Distributed Systems.
• Experience using Machine Learning techniques. Exposure to Timeseries, Causality, and NLP (especially LLM) is a big plus.
• 8+ experience in design, algorithms, and data structures - Expertise with the following languages is a must - Java, Python, and SQL.
• Proven leadership skills with an ability to deliver under tight deadlines.
• Proven ability to collaborate with many cross-functional teams with an emphasis on end-to-end delivery.
• Experience with deep learning frameworks such as PyTorch and TensorFlow, Huggingface Transformers, or related is a big plus.
• Thorough understanding of Dev Ops and ML Ops best practices like algorithms/models monitoring and orchestration.
• Capacity to become a self-driven individual contributor and an excellent team player when the teams and the business requires it.

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.

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