Software Engineer, ML Infrastructure

About this role

## About Ideogram

Ideogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.

We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship.

Explore [Ideogram 4.0](https://ideogram.ai/models/4.0/), [Enterprise](https://ideogram.ai/enterprise/), [API](https://ideogram.ai/api-learn/), [Open Source](https://ideogram.ai/licensing/), [Character](https://ideogram.ai/features/character) and [Custom Models](https://ideogram.ai/features/custom-models/) blog posts, and try Ideogram at [ideogram.ai](http://ideogram.ai).

## About The Role

As a Software Engineer, ML Infrastructure at Ideogram, you'll build the systems that power training and serving for our generative AI models at scale. You'll work across the stack, from designing distributed training infrastructure to optimizing inference pipelines that serve millions of users, with a relentless focus on reliability, speed, and efficiency. We're looking for someone who combines deep systems expertise with a builder's mindset, strong technical ownership, and the ability to move fast in an evolving AI landscape.

## What We're Looking For

Technical Excellence

- 1-4 years developing and shipping large-scale production infrastructure.
- Experience designing large, highly available distributed systems with Kubernetes/GCP, and GPU/TPU workloads on those clusters.
-...