Qualifications

• 5-7 years of experience in security engineering, infrastructure security, or application security within large-scale systems/cloud environments (GCP, AWS, or Azure).
• Proficiency in software and systems engineering, particularly in Linux, networking, infrastructure-as-code, and programming languages (Python, Go, Rust).
• In-depth understanding of security challenges in machine learning platforms and protection of high-value model weights/intellectual property.
• Ability to perform architectural security reviews and adapt to new environments quickly.
• Focus on practical solutions that deliver real-world impact, particularly under pressure.
• End-to-end ownership of deliverables, from initial requirements to autonomous execution.

Responsibilities

• Design and deploy security architectures across distributed GPU clusters and network infrastructure.
• Implement security in software development practices alongside Infrastructure and Research teams.
• Manage identity and access, data governance, and encryption for large datasets and proprietary information.
• Conduct threat modeling, vulnerability assessments, and establish proactive threat detection tailored for ML infrastructure.
• Assist Forward Deployed teams to navigate security and compliance in customer environments, ensuring practical secure solutions.

Benefits

• Health, dental, and vision insurance.
• 401(k) with company match.
• Generous vacation and paid time off policies.
• Professional development opportunities.
• Flexible work hours and remote work options.