Security Engineer: ML & GPU Infra (Hybrid SF)

Higgsfield AI; San Francisco (CA); Hybrid; USD 200,000 - 300,000; Full time

Benefits offered by this job

Equity

Medical insurance

401(k) matching

Bonus eligibility

Job summary

Higgsfield AI is seeking a highly technical MTS, ML Security to own security across GPU clusters and AI/ML infrastructure. You will work with Security, ML, and Infrastructure teams to design, implement, and operate controls protecting models, data, and infrastructure.

The role requires balancing security, performance, and reliability in a fast-moving AI environment. The ideal candidate brings hands-on security engineering experience, practical GPU/ML infra knowledge, and the ability to drive

Qualifications

• Strong hands-on security engineering experience.
• Deep understanding of Linux, Kubernetes, networking and cloud security.
• Practical experience securing GPU clusters or distributed AI/ML infra.
• Experience designing security controls across complex environments.
• Knowledge of IAM, encryption, secrets management and least-privilege.

Responsibilities

• Own GPU cluster security across training and inference in cloud and datacenter environments.
• Harden GPU hosts, drivers, runtimes, Kubernetes clusters and isolation mechanisms.
• Secure training/inference by enforcing tenant isolation and access controls.
• Design controls to protect datasets, model weights, and customer data.
• Collaborate with ML and Platform teams to embed security into workflows.

Skills

Security engineering

Kubernetes & Linux

Cloud security

Vendor security assessments

Python/Go/Bash

Tools

Kubernetes

Linux

Python

Job description

Higgsfield AI is seeking a highly technical MTS, ML Security to own security across GPU clusters and AI/ML infrastructure. You will work with Security, ML, and Infrastructure teams to design, implement, and operate controls protecting models, data, and infrastructure.

The role requires balancing security, performance, and reliability in a fast-moving AI environment. The ideal candidate brings hands-on security engineering experience, practical GPU/ML infra knowledge, and the ability to drive