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Member of Technical Staff, ML Security

Higgsfield AI· Product Engineering
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Hybrid (San Francisco Bay Area, USA)$200k - $300k + equity + bonusFull-timePosted yesterday

About the role

Technical role focused on security across GPU clusters and AI/ML infrastructure, from model training to inference and production deployment, within Higgsfield AI’s Security team.

Responsibilities

  • Own the security of GPU clusters supporting distributed training and production inference across cloud and rented datacenter environments.
  • Harden GPU hosts, operating systems, drivers, container runtimes, Kubernetes clusters, and workload scheduling configurations; reduce privileged access and unnecessary exposure.
  • Secure distributed training environments and GPU workloads through isolation, access controls, and data movement restrictions. Validate isolation between tenants and workloads across compute, networking, and storage, including shared GPU environments where applicable.
  • Design and implement controls to protect sensitive datasets, model checkpoints, weights, and customer data.
  • Strengthen inference security through tenant isolation, service authorization, secure model loading.
  • Partner with ML and Platform Engineering teams to integrate security into infrastructure design and development workflows.
  • Lead technical security assessments of GPU infrastructure providers, datacenter operators, and other AI security vendors that process Higgsfield data and support AI workloads.
  • Evaluate vendor architecture and evidence covering tenant isolation, privileged access, data handling and retention, use of customer data for model training, encryption, vulnerability management, and incident response.
  • Translate security requirements into enforceable technical controls, including approved configurations, and continuous checks for configuration drift.
  • Track internal and vendor security findings to closure with accountable owners and deadlines, validate remediation, and escalate unmet requirements. Document any approved exceptions with compensating controls and expiration dates.
  • Design, implement, and maintain security controls across Linux, Kubernetes, cloud infrastructure, networks, and third party datacenter environments.
  • Secure infrastructure provisioning, configuration management, and access to third-party infrastructure providers. Restrict and audit vendor and administrator access to cluster management interfaces and production systems.
  • Implement least-privilege access, workload identity, secrets management, encryption, and auditable access controls.
  • Identify and remediate vulnerabilities and configuration risks across production systems, including GPU hosts, drivers, and container runtimes, coordinating changes with infrastructure owners to maintain service reliability.
  • Develop and maintain detection and response capabilities for infrastructure and AI-specific security threats, including unauthorized GPU workloads, privilege escalation, and suspicious data transfers.
  • Investigate and respond to potential credential compromise, unauthorized data access, model theft, and compromised workloads.
  • Partner cross-functionally to implement practical security improvements that account for the performance, scalability, and reliability requirements of GPU workloads.

Qualifications

  • Strong hands-on experience in Security Engineering, Infrastructure Security, Platform Security, or a related technical discipline.
  • Deep understanding of Linux, Kubernetes, networking, and cloud infrastructure security.
  • Practical experience securing or operating GPU clusters or distributed AI/ML infrastructure, with an understanding of training and inference workloads, GPU drivers and runtimes, and workload isolation.
  • Experience designing and implementing security controls across complex, distributed production environments.
  • Strong knowledge of identity and access management, workload isolation, encryption, secrets management, and least-privilege principles.
  • Experience conducting technical vendor security assessments, evaluating supporting evidence, and driving remediation with external providers.
  • Ability to identify, investigate, and remediate security vulnerabilities and infrastructure threats.
  • Proficiency in scripting or programming languages such as Python, Go, or Bash.
  • Experience partnering with Infrastructure, Platform, or ML Engineering teams to implement security solutions.
  • Strong technical ownership, sound judgment, and the ability to prioritize security risks in a fast-paced environment.
  • A hands-on, collaborative approach with the ability to independently drive security initiatives from design through deployment, verify that controls work in production, and hold internal teams and vendors accountable for agreed security requirements.

Skills

Required:GPU infrastructure securityLinux administrationKubernetes securityCloud securityIdentity and access managementVendor security assessmentsScripting languages

Benefits

  • We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks.
  • Equity: eligible to participate in the company’s stock option program.
  • Bonus: Bonus eligible and may participate in the Company's discretionary annual bonus program.
Last updated Oct 25, 2026. Interested? Apply on the company site.
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