Infrastructure Engineer, Security

Thinking Machines Lab•San Francisco, CA

About The Position

Thinking Machines is hiring an infrastructure engineer to own and evolve the security infrastructure supporting its foundation models. The role spans compute, storage, networking, and data platforms, ensuring systems are secure, reliable, and scalable. The engineer will shape security controls, architecture, and tooling so security is built into the platform by default, while partnering with research and product teams to enable rapid work and protect models, data, and environments.

Requirements

Bachelor’s degree or equivalent experience in engineering or a similar field.
Strong background with containers and orchestration, such as Kubernetes, and container security practices including namespaces, network policies, pod security, and admission controls.
Practical experience with Infrastructure as Code, such as Terraform, including secure provisioning patterns for networks, IAM, and shared services.
Solid understanding of cloud networking and security, including VPCs, load balancers, service discovery, mTLS, firewalls, and zero-trust-style architectures.
Proficiency with a systems language such as Rust and scripting in Python to build platform components and internal tools.
Evidence of owning complex, production-critical systems and debugging issues across infrastructure, security, and application layers.

Nice To Haves

Experience with ML infrastructure, GPU clusters, or large-scale training environments, including schedulers, job queues, shared storage, and multi-tenant clusters.
Background in AI labs, HPC environments, or ML-heavy organizations where security and performance are both first-class concerns.
Experience profiling and tuning high-throughput systems and reasoning about the cost of additional security layers.
Talks, blogs, or publications on infrastructure security, distributed systems, or performance engineering.
Open-source contributions to security, orchestration, observability, or infrastructure tooling.
Familiarity with securing specialized hardware such as GPUs and TPUs and integrating it into training and inference pipelines.

Responsibilities

Architect security patterns for platforms and services, including network segmentation, service-to-service authentication, RBAC, and policy enforcement in Kubernetes and cloud environments.
Manage identity, access, and secrets for people and services, including workload and cross-cloud identity, least-privilege IAM, and secrets management.
Build secure platforms for data ingestion, processing, and curation, including classification, encryption, access controls, and safe sharing patterns across teams.
Write threat models and review designs with researchers and engineers to help them deliver features and experiments safely and at scale.
Automate security checks and build guardrails, including policy-as-code, secure infrastructure baselines, CI/CD validation, and tools that make secure practices easier.