About Citadel AI
Citadel AI builds products to test and monitor high-risk AI systems. Our mission is to make the world’s AI systems more reliable and trustworthy.
Our company is located in Tokyo, but we have an international team and global customers. We’re building a world-class engineering team here – our founding engineers have previously worked at leading tech companies such as Google Brain, Waymo, PayPal, and Toyota.
This is a unique opportunity to build new products for a global market from Tokyo. As one of Citadel AI’s first engineers, you’ll have significant impact and ownership over our startup’s trajectory. Our company is extremely well funded, and our first investor was The University of Tokyo.
About the role
We’re hiring backend engineers to work with our small, full-stack team to build products to test, monitor, and improve the reliability of machine learning systems.
You’ll be responsible for building our product’s backend and working with web servers, SQL databases, parallel computing, API design, multi-cloud architecture, integrating with external services (e.g. SSO), and going as deep into our ML stack as you can.
Our backend is primarily in Python. Some technologies we use are: Docker, PostgreSQL, Redis, RQ, Gunicorn, Flask, TensorFlow Extended, Pytest, and many Python ML libraries.
No ML expertise is required for this role, though we hope you’re interested to dive deep into the emerging space of MLOps / trustworthy ML / responsible AI.
As an early employee, you’ll own a significant equity stake in addition to your base salary.
Our company, technology, and market are new and changing rapidly, so a large part of the job is to adapt and learn new things. We value learning fast over pre-existing knowledge (“slope is more important than y-intercept”).
You should have at least 1 year of backend software engineering experience. We don’t require past experience with specific programming languages or frameworks.
English is required, Japanese is optional. We prioritize candidates in Tokyo, but may consider remote for exceptional candidates.
Nice-to-have: you can work full-stack, you’ve worked at a startup before, or you have experience with production machine learning.
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