Applied AI Researcher

About the company

Cato Networks provides a cloud-native SASE platform that converges SD-WAN, global backbone, WAN/LAN security (ZTNA, SSE, XDR, IPS), AI-driven automation, and managed connectivity for sites, users, and cloud resources.

About this role

<div class="content-intro"><p><strong>Welcome to the future of cloud networking and security!&nbsp;&nbsp;</strong></p> <p><span data-olk-copy-source="MessageBody">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, Exabeam, Trusteer and more). Cato’s unique technology inspired a brand-new product category, later named “SASE” by Gartner and a market expected to reach $28.5 billion by 2028.<br><br>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!</span></p> <p>&nbsp;</p></div><div class="p-rich_text_section"> <div id="message-list_1761841251.482129" class="c-virtual_list__item" data-qa="virtual-list-item" data-item-key="1761841251.482129"> <div class="c-message_kit__background c-message_kit__background--hovered p-message_pane_message__message c-message_kit__message" data-qa="message_container" data-qa-unprocessed="false" data-qa-placeholder="false"> <div class="c-message_kit__hover c-message_kit__hover--hovered" data-qa-hover="true"> <div class="c-message_kit__actions c-message_kit__actions--default"> <div class="c-message_kit__gutter"> <div class="c-message_kit__gutter__right" data-qa="message_content"> <div class="c-message_kit__blocks c-message_kit__blocks--rich_text"> <div class="c-message__message_blocks c-message__message_blocks--rich_text" data-qa="message-text"> <div class="p-block_kit_renderer" data-qa="block-kit-renderer"> <div class="p-block_kit_renderer__block_wrapper p-block_kit_renderer__block_wrapper--first"> <div class="p-rich_text_block"> <div class="p-rich_text_section"> <div class="p-rich_text_section"> <div id="message-list_1761841251.482129" class="c-virtual_list__item" data-qa="virtual-list-item" data-item-key="1761841251.482129"> <div class="c-message_kit__background c-message_kit__background--hovered p-message_pane_message__message c-message_kit__message" data-qa="message_container" data-qa-unprocessed="false" data-qa-placeholder="false"> <div class="c-message_kit__hover c-message_kit__hover--hovered" data-qa-hover="true"> <div class="c-message_kit__actions c-message_kit__actions--default"> <div class="c-message_kit__gutter"> <div class="c-message_kit__gutter__right" data-qa="message_content"> <div class="c-message_kit__blocks c-message_kit__blocks--rich_text"> <div class="c-message__message_blocks c-message__message_blocks--rich_text" data-qa="message-text"> <div class="p-block_kit_renderer" data-qa="block-kit-renderer"> <div class="p-block_kit_renderer__block_wrapper p-block_kit_renderer__block_wrapper--first"> <div class="p-rich_text_block"> <div class="p-rich_text_section"> <div class="p-rich_text_section"> <div id="message-list_1761841251.482129" class="c-virtual_list__item" data-qa="virtual-list-item" data-item-key="1761841251.482129"> <div class="c-message_kit__background c-message_kit__background--hovered p-message_pane_message__message c-message_kit__message" data-qa="message_container" data-qa-unprocessed="false" data-qa-placeholder="false"> <div class="c-message_kit__hover c-message_kit__hover--hovered" data-qa-hover="true"> <div class="c-message_kit__actions c-message_kit__actions--default"> <div class="c-message_kit__gutter"> <div class="c-message_kit__gutter__right" data-qa="message_content"> <div class="c-message_kit__blocks c-message_kit__blocks--rich_text"> <div class="c-message__message_blocks c-message__message_blocks--rich_text" data-qa="message-text"> <div class="p-block_kit_renderer" data-qa="block-kit-renderer"> <div class="p-block_kit_renderer__block_wrapper p-block_kit_renderer__block_wrapper--first"> <div class="p-rich_text_block"> <div class="p-rich_text_section"> <p data-start="694" data-end="711">As part of this exciting journey, Cato recently joined forces with <strong data-start="472" data-end="488">Aim Security</strong> — a fast-growing innovator redefining how organizations secure and build with AI.<br data-start="570" data-end="573">Backed by Cato’s global reach and powered by Aim’s startup energy, we’re building the future of AI Security together.<br><br>We are on a mission to enable enterprises to adopt AI safely and securely. Our approach combines advanced AI research with practical implementation to offer seamless integration and protection for our clients' AI based tools and infrastructure.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div id="message-list_bottomSpacer" class="c-virtual_list__item" data-qa="virtual-list-item" data-item-key="bottomSpacer"></div> <p>We are looking for a <strong>Senior Data Scientist / Applied AI Researcher</strong> with deep expertise in NLP and LLM-based systems, and the ability to operate across the full lifecycle, from problem formulation and research design to production deployment and real-world iteration.</p> <p>You won’t be working on isolated experiments. You’ll be part of a multidisciplinary team that owns the system end-to-end and is responsible for how it behaves under real production traffic.</p> <p>This role requires strong scientific discipline and the maturity to balance innovation with practical constraints.</p> <br><br><br><strong>What you’ll do</strong></div> <ul> <li><strong>End-to-End Ownership:</strong> Lead AI security solutions from problem formulation and research design through model development, evaluation, and production deployment. Ensure solutions are measurable, reliable, and effective under real-world traffic.</li> <li><strong>Drive Technical Direction:</strong> Take responsibility for ambiguous AI security problems, propose thoughtful approaches, and drive structured experimentation and deep model analysis.</li> <li><strong>Build fo