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Infrastructure and Reliability Engineer - Developer Platform
TypeSafe AI
San Francisco, USA
Full-time
Senior · 5+ years experience
Onsite
USD 180000-280000 yearly / year
Discovered 1 weeks ago
PythonTypeScriptNext.jsTailwind CSSKubernetesClaude Code
Free
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PythonTypeScriptNext.js
Role Overview
As an ML infrastructure and reliability engineer, you will join the team responsible for building and maintaining TypeSafe’s API platform for inference. These APIs will be user facing, latency sensitive, and (once we ship) have uptime, reliability and backwards compatibility requirements.
The role is wide ranging and you will wear many hats. Responsibilities include:
Create robust infrastructure for serving inference across multiple cloud providers
Work to ensure inference infrastructure and services are reliable and have low error rates
Create and maintain infrastructure for monitoring and alerting on requests, improving our debugging and operations stance
Ramp up oncall engineers on error handling in production via playbooks, mentorship, “fire drill” exercises, etc.
Our tech stack is primarily Python. We also use TypeScript, Next.js, and Tailwind CSS for frontend, with Kubernetes for orchestration. We empower developers to use any tooling they find helpful for getting their job done, including Claude Code and Cursor.
Key Skills for This Role
PythonTypeScriptNext.jsTailwind CSSKubernetesClaude Code
Full Job Posting
About the Role
As an ML infrastructure and reliability engineer, you will join the team responsible for building and maintaining TypeSafe’s API platform for inference. These APIs will be user facing, latency sensitive, and (once we ship) have uptime, reliability and backwards compatibility requirements.
The role is wide ranging and you will wear many hats. Responsibilities include:
Create robust infrastructure for serving inference across multiple cloud providers
Work to ensure inference infrastructure and services are reliable and have low error rates
Create and maintain infrastructure for monitoring and alerting on requests, improving our debugging and operations stance
Ramp up oncall engineers on error handling in production via playbooks, mentorship, “fire drill” exercises, etc.
Our tech stack is primarily Python. We also use TypeScript, Next.js, and Tailwind CSS for frontend, with Kubernetes for orchestration. We empower developers to use any tooling they find helpful for getting their job done, including Claude Code and Cursor.
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