Software Engineer, ML Data Infrastructure
IdeogramTorontoPosted 7 April 2026
Job Description
Software Engineer, ML Data Infrastructure
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 3.0 https://ideogram.ai/features/3.0, Canvas https://ideogram.ai/features/canvas, and Character https://ideogram.ai/features/character blog posts, and try Ideogram at ideogram.ai http://ideogram.ai.
ABOUT THE ROLE
We're seeking an experienced engineer to join our team as a Software Engineer, ML Data Infrastructure. You’ll collaborate with exceptional engineers to build cutting-edge AI design experiences that delight millions of users.
You'll thrive here if you're excited about:
- Tackling complex technical challenges collaboratively, from scaling distributed systems to enabling new generative media experiences
- Building robust data infrastructure that powers foundation models at petabyte scale, ensuring reliability and performance across multi-modal training pipelines
- Optimizing data processing workflows for massive throughput, working hands-on with distributed systems, TPU infrastructure, and large-scale storage solutions
- Partnering with research scientists to understand data requirements and translating them into production-grade systems that accelerate model development cycles
WHAT WE'RE LOOKING FOR
Technical Excellence
- 2-5 years developing and shipping large-scale distributed systems with proven ability to manage complexity through thoughtful abstractions and scalable design
- Strong fundamentals in data structures, algorithms, and distributed systems
- Strong understanding of databases and data storage architectures.
- Hands-on experience with large-scale data processing systems.
- Demonstrated ability to drive projects from 0 to 1, including scoping, execution, and iteration.
Ownership
- Deep sense of ownership - proactively identifies opportunities, suggests improvements, and acts on them
- Thrives in fast-moving, ambiguous environments with a strong bias toward action
- Asks great questions, thinks from first principles, and seeks out resources to deepen understanding
OUR STACK
Our backend infrastructure is primarily written in Python and makes use of the following technologies (experience with them is helpful but not strictly required):
- Kubernetes
- GCP, Google Bigtable, Google BigQuery, Google Spanner, Google Pub/Sub
- Docker & Terraform
OUR CULTURE
We’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.
Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.
Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.
WHAT WE OFFER
💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success.
🌴 4 weeks of vacation to ... (truncated, view full listing at source)
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