Security Engineer, ML Infrastructure

LinuxCareers; San Francisco (CA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Discretionary annual bonus

Stock options

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Job summary

Higgsfield AI is seeking a Security Engineer focused on ML Infrastructure to own security across GPU clusters and AI/ML infrastructure from training to production deployment. You will harden compute environments, assess vendor security, and implement technical controls across cloud and datacenter datacenters.

Responsibilities include securing distributed training workloads, validating tenant isolation, and strengthening model loading security, with leadership in vendor security assessments and

Qualifications

• Strong hands-on experience in Security Engineering, Infrastructure Security, or related discipline.
• Deep understanding of Linux, Kubernetes, networking, and cloud infrastructure security.
• Experience securing GPU clusters or distributed AI/ML infrastructure.

Responsibilities

• Own the security of GPU clusters supporting distributed training and production inference across cloud and rented datacenters.
• Secure environments with isolation, access controls, and data movement restrictions across compute, networking, and storage.
• Design and implement controls to protect datasets, model checkpoints, weights, and customer data; strengthen inference security.
• Lead security assessments of GPU infrastructure providers and AI vendors; evaluate vendor architecture for tenant isolation and incident response.
• Develop and maintain security controls across Linux, Kubernetes, cloud infra, networks, and third-party datacenters; build detection and response capabilities.

Skills

Security Eng

Linux

Kubernetes

Cloud security

Scripting

Job description

Higgsfield AI is a generative AI company building AI-powered video creation and creative tools. This role is a Security Engineer focused on ML Infrastructure, responsible for owning security across GPU clusters and AI/ML infrastructure from model training to inference and production deployment, including securing compute environments, assessing vendor security, and implementing technical controls.

What You'll Do

• Own the security of GPU clusters supporting distributed training and production inference across cloud and rented datacenter environments, including hardening GPU hosts, operating systems, drivers, container runtimes, and Kubernetes clusters
• 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
• Design and implement controls to protect sensitive datasets, model checkpoints, weights, and customer data; strengthen inference security through tenant isolation, service authorization, and secure model loading
• Lead technical security assessments of GPU infrastructure providers, datacenter operators, and AI security vendors; evaluate vendor architecture covering tenant isolation, privileged access, data handling, encryption, and incident response
• Design, implement, and maintain security controls across Linux, Kubernetes, cloud infrastructure, networks, and third-party datacenters; develop detection and response capabilities for infrastructure and AI-specific security threats

What You Need

• Strong hands-on experience in Security Engineering, Infrastructure Security, Platform Security, or 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 understanding of training and inference workloads, GPU drivers, runtimes, and workload isolation
• Experience designing and implementing security controls across complex, distributed production environments
• Proficiency in scripting or programming languages such as Python, Go, or Bash

Nice to Have

• Experience conducting technical vendor security assessments and driving remediation with external providers
• Experience partnering with Infrastructure, Platform, or ML Engineering teams to implement security solutions
• Knowledge of identity and access management, workload isolation, encryption, secrets management, and least-privilege principles

Base salary $200,000-300,000 depending on experience, skills, scope, and location; bonus eligible with discretionary annual bonus program; equity through stock option program; comprehensive benefits including medical, dental, vision insurance, 401(k) with company matching