Welcome to the future of cloud networking and security!
Cato Networks is the first company to converge enterprise networking and security into one centralized and global service that is delivered by cloud. It is led by networking and security pioneer Shlomo Kramer (Check Point, Imperva) and early investor (Palo Alto Networks, Exabeem, Trusteer and more). Cato’s unique technology inspired a brand-new product category, later named “SASE” by Gartner and a market expected to reach $25 billion by 2027.
This is your opportunity to get on the rocket ship and join a company that is building a cutting-edge enterprise network and secure cloud platform, and is on a fast track to becoming the worldwide market leader – don’t miss it!
Leveraging rich, real-time data from our global backbone and the Cato Cloud data warehouse, you will apply advanced analytics, machine learning, and deep learning techniques to solve complex cybersecurity and networking challenges. You will also collaborate closely with internal business departments to accelerate AI adoption and develop intelligent systems that deliver operational efficiencies and strategic value across the company.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
- Lead the design, development, and deployment of machine learning models and AI features that enhance Cato’s security and networking products
- Analyze large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
- Collaborate cross-functionally with product, engineering, sales, and support teams to translate business needs into AI solutions
- Drive AI adoption internally by working with business units to implement generative AI and other intelligent systems that deliver measurable impact
- Define and track success metrics to ensure AI solutions meet performance and business goals
- Minimum 3 years of professional experience in Data Science roles
- Hands-on experience in networking and/or cybersecurity domains
- Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
- Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
- Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
- Excellent analytical, problem-solving, and communication skills
- Self-motivated, collaborative, and able to work independently
- Experience building agentic systems using Retrieval-Augmented Generation (RAG), including tool orchestration, benchmarking frameworks, and vector databases (e.g., FAISS, Pinecone)
- Prior experience working in a fast-paced, high-growth environment
- Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field
Similar Jobs
What We Do
WE ARE SASE
