Senior Machine Learning Engineer - Cybersecurity

Our Purpose At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here. About Us SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters. Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity. What Are We Looking For? We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes. As a Senior ML Engineer you will join our Static AI team which develops state-of-the-art ML models that operate on millions of machines worldwide, making sub-second decisions to stop malware before it runs. We bring together cross-functional skill sets, including data science, ML engineering, and software engineering, to research, develop, ship, and support ML malware detection engines across Windows, Mac, and Linux machines and cloud environments. What Will You Do? Primary responsibilities include : Data pipeline architecture: Design, build, and maintain scalable data pipelines to handle millions of data points from internal and external sources ML infrastructure: Develop and optimize the infrastructure required for training, evaluating, and deploying ML models at scale Cross-functional Collaboration: Work closely with Data Scientists and Software Engineers to translate research into production-ready detection engines System optimization: Build and improve analytics systems that learn from a wide variety of data sources to enhance our existing ML models Production support: Ensure the reliability and performance of ML malware detection engines across Windows, Mac, Linux, and cloud environments "Production experience" - good level of coding, tests, dealing with CI You will also be encouraged to write white papers, blogs, and articles or present in meetups / conferences (but only if you wish to) What Skills and Knowledge Will You Bring? Ideal candidates will have: Degree in Computer Science or Mathematics, or equivalent experience Experience with collecting and building large datasets for training machine learning models Producing, deploying and running ML in production environments Experience working with Big data technologies, such as Spark/Databricks, Hadoop, and others Ability to work collaboratively to translate business requirements into technical solutions Willingness and ability to work in a diverse, globally distributed team The ability to work on difficult problems independently Strong communication skills. Our team relies on strong communication, since we have a diverse and sometimes exclusive set of skills, yet our end product relies on all team members. Thus, we need our team members to be able to communicate with people outside our team (with a wide range of b ... (truncated, view full listing at source)