Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market. Position Overview We are looking for a highly skilled Staff Machine Learning Software Engineer with a passion for building robust and scalable systems to power Stellar Cyber’s Open XDR platform. In this role, you will be at the forefront of data-intensive cybersecurity and machine learning software architecture innovation, responsible for developing the foundational components that enable effective and efficient cybersecurity operations for our customers. Key Responsibilities - Design and implement scalable data processing components and supporting features for Stellar Cyber’s cybersecurity applications, including but not limited to, threat detections, incident correlation, threat intelligence, and asset management. - Candidates who successfully pass all the interviews will be assigned to a project area in need. - Monitor and resolve production stability issues related to the aforementioned components and features. - Collaborate closely with machine learning / security researchers, UI / UX, and product management to ensure the design and implementation to align with evolving product needs and business goals.

Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market. Position Overview We are looking for a highly skilled Senior Staff Machine Learning Software Engineer with a passion for building robust and scalable systems to power Stellar Cyber’s Open XDR platform. In this role, you will be at the forefront of data-intensive cybersecurity and machine learning software architecture innovation, responsible for developing the foundational components that enable effective and efficient cybersecurity operations for our customers. Key Responsibilities - Design and implement scalable data processing components and supporting features for Stellar Cyber’s cybersecurity applications, including but not limited to, threat detections, incident correlation, threat intelligence, and asset management. - Candidates who successfully pass all the interviews will be assigned to a project area in need. - Monitor and resolve production stability issues related to the aforementioned components and features. - Collaborate closely with machine learning / security researchers, UI / UX, and product management to ensure the design and implementation to align with evolving product needs and business goals.

• Design, develop, and maintain scalable backend services using Python • Build and optimize reliable data pipelines for ingestion, transformation, and analytics • Develop and maintain RESTful APIs using FastAPI • Work extensively with Snowflake and Databricks for data storage, querying, and optimization • Collaborate with product and engineering teams to design data models, APIs, and system integrations • Ensure performance, scalability, reliability, and observability of data services • Implement best practices for code quality, testing, monitoring, and documentation • Participate in code reviews, architectural discussions, and technical decision-making • Troubleshoot and resolve production issues related to data workflows and backend services

• Lead the design of robust, scalable solutions for integrating Cornelis Networks' platform and fabric management software with Kubernetes. • Build and maintain custom Kubernetes Operators and Controllers in Go to manage the lifecycle of our software and hardware components within a cluster. • Develop solutions that allow for the seamless orchestration of our high-performance fabric services and platform management tools alongside other containerized workloads. • Work on extending Kubernetes for managing specialized hardware, scheduling, and networking requirements unique to HPC and AI workloads. • Partner with the core platform, fabric, and hardware teams to ensure a cohesive and performant end-to-end solution. • Engage with the open-source community and contribute to relevant projects within the cloud-native ecosystem. • Author high-quality technical documentation and champion best practices for software development in a cloud-native environment.