T

Thinking Machines Lab

Researches AI and builds tools to customize models

Infrastructure Engineer - Security

Security Engineering & ArchitectureConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent experience in engineering or a similar field.
  • A strong background with containers and orchestration, such as Kubernetes, and securing them through namespaces, network policies, pod security, and admission controls.
  • Practical experience with Infrastructure as Code, such as Terraform, including secure patterns for provisioning networks, identity and access management, and shared services.
  • A solid understanding of cloud networking and security, including virtual private clouds, load balancers, service discovery, mutual TLS, firewalls, and zero-trust 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, including debugging issues across infrastructure, security, and application layers.

Responsibilities

  • Architect security patterns for platforms and services, including network segmentation, service-to-service authentication, role-based access control, 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 identity and access management, 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 ship features and experiments safely and at scale.
  • Automate security checks and build guardrails, including policy as code, secure infrastructure baselines, validation in continuous integration and continuous delivery, and tools that make the secure path the easiest one.

Desired Qualifications

  • Experience with machine learning infrastructure, GPU clusters, or large-scale training environments, including schedulers, job queues, shared storage, and multi-tenant clusters.
  • A background in AI labs, high-performance computing environments, or machine-learning-heavy organizations where security and performance are both first-class concerns.
  • Experience profiling and tuning high-throughput systems, and the ability to reason 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.

About the Company

Thinking Machines Lab

Researches AI and builds tools to customize models

Thinking Machines Lab researches and builds AI systems, aiming to make AI more widely understood, customizable, and capable. It publishes much of its research openly on its Connectionism blog, starting with work on making AI models give consistent answers to the same question. Its first product, Tinker, lets researchers and developers fine-tune open-weight AI models on their own data while Thinking Machines runs the computing clusters behind it, so customers focus on their data and training methods instead of managing hardware and pay for the computing they use. Former OpenAI chief technology officer Mira Murati founded the lab in 2025, and it is based in San Francisco.

Company size
201-500
Company stage
Series A
Total funding
$7B
Headquarters
San Francisco, CA
Founded
2024

Recently Posted Jobs

Explore more opportunities at Thinking Machines Lab

See more jobs