Causal Labs
Member of Technical Staff — Security Engineering
San Francisco +1 · On-site · Staff · Full-time · Posted Jul 30, 2026
- Location
- San Francisco
Singapore
About the job
Designs and operates security across Causal Labs’ infrastructure, machine-learning systems, and customer deployments, protecting data, model weights, and software while supporting rapid engineering work.
What you'll do
- Architect cloud isolation, secure data transmission, access controls, and encryption for large-scale storage.
- Protect model weights and training pipelines; defend against AI-specific threats such as data poisoning, model extraction, and adversarial inputs.
- Implement enterprise identity, audit logging, compliance controls, and automated security testing across deployment workflows and customer APIs.
What they ask for
- Hands-on experience securing production cloud environments (AWS, GCP, or Azure) or large-scale distributed systems; practical mastery of IAM, network perimeters, KMS/encryption, and secrets management.
- Experience with Linux, networking, Docker, Kubernetes, Terraform or Pulumi, and proficiency in Python, Go, or Rust.
- Practical understanding of ML platform security, including model-weight protection, distributed training, data lineage or poisoning, and AI-specific threats.
- Ability to conduct security reviews and own work from threat modeling through deployment and monitoring.
Tools
AWS, GCP, Azure, Linux, Docker, Kubernetes, Terraform, Pulumi
AI focus
Secures the Large Physics Model, its weights and training pipelines, and defends against AI-specific threats including adversarial inputs, model extraction, and data memorization or regurgitation.
Model-written summary · the original posting is authoritative