Senior Software Engineer | Machine Learning Infrastructure

ExtraHop is on a mission to protect and propagate trust by revealing the cybertruth: the truth about the attackers already inside an organization’s network, the truth about what they’re doing, and how to stop them at top speed. We partner with every customer, every day, to reveal it. Are you ready to join us?

ExtraHop offers an exciting, high-energy, and versatile environment in which people are encouraged and supported to collaborate on industry-leading technology and create a world-class engineering team, while they develop and enrich their individual growth. And we're doing it with creativity, intellectual curiosity, and deep critical thinking.

The Machine Learning Infrastructure team owns the tools that empower the development of new machine learning models and data intelligence at Extrahop. Scalability, efficiency and experimentation is the lifeblood of machine learning. Come help build tools that simplify the processes that make all this possible. 

Our goal on the Machine Learning Infrastructure team is to make it fast, easy, and cost effective to design, code, deploy, perform experiments, and to develop and support the production environment to deliver cybersecurity detections in a timely manner. As an engineer on this team, you will design and build infrastructure and tooling to support ongoing research and scalability efforts. 

We have a global and diverse user base—we believe in actively investing in a diverse engineering organization. We are seeking highly talented software engineers from all backgrounds, who offer dynamic perspectives, influences, and experiences. Are you as passionate as we are about positive culture and amazing technology? If you are, we can't wait to chat with you.

Requirements

• Lead the architecture, design, development, and deployment of machine learning systems, ensuring they meet performance, scalability, and security requirements.
• Provide assistance and mentorship to software engineering teams, guiding them in best practices for infrastructure design, microservices architecture, and modern software engineering techniques.
• Design and develop secure and scalable models in Python.
• Stay current with industry trends, emerging technologies, and best practices related to machine learning infrastructure and software development.
• Collaborate closely and effectively with cross-functional teams including data science research, detection engineering, cloud services and quality assurance.
• Participate in code reviews, design discussions, and provide insightful feedback to team members to maintain code quality and adherence to best practices.
• Utilize cybersecurity best practices to enhance the security …