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About the Role

We are building a Large Physics foundation Model (LPM) to achieve general causal intelligence, enabling AI to predict and alter future events. This role is crucial for designing and operating the security posture across our entire engineering stack, ensuring the security of research environments, proprietary model weights, software infrastructure, and customer integrations while maintaining engineering velocity.

Responsibilities

Design and deploy robust security architectures across distributed GPU clusters, shared compute platforms, and network infrastructure.
Drive secure software development lifecycle (SDLC) practices, integrating security into pipelines, APIs, and orchestrators.
Own identity and access management (IAM), data governance, and encryption strategies for petabyte-scale data and model checkpoints.
Conduct threat modeling, vulnerability assessments, and implement proactive threat detection and incident response tooling for ML infrastructure.
Support Forward Deployed teams by navigating security and compliance constraints in customer environments.

Requirements

Demonstrated experience in security engineering, infrastructure security, or application security within large-scale distributed systems or cloud environments (GCP, AWS, or Azure).
Strong systems and software engineering background including Linux, networking, and infrastructure-as-code.
Proficiency in programming languages such as Python, Go, or Rust.
Deep understanding of security challenges associated with machine learning platforms, distributed training, and protecting model weights/IP.
Comfort working directly with complex systems, conducting architectural security reviews, and adapting quickly to new constraints.
Ability to deliver practical, real-world solutions under pressure.
Proven ability to own deliverables end-to-end, from requirements through autonomous execution.

Skills

Security Engineering
Infrastructure Security
Application Security
Distributed Systems Security
Cloud Security (GCP, AWS, Azure)
Linux
Networking
Infrastructure-as-Code
Python
Go
Rust
Machine Learning Security
Threat Modeling
Vulnerability Assessment
Incident Response
Identity and Access Management (IAM)
Data Governance
Encryption

Location

Remote

Work Type

Full-time

Experience Level

Mid-level
Senior

About the Company

Our mission is general causal intelligence; AI that is capable of (1) predicting the future and (2) identifying the actions to alter it.
We are building a Large Physics foundation Model (LPM) because physical systems, unlike text or images, are governed by verifiable cause and effect.
We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.
Our founding team has built and deployed AI against the physical world in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.