Software Engineer, ML Infrastructure
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Software Engineer, ML Infrastructure
Location
Toronto
Experience
Mid
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
## 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 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.
- Experience in deploying, supporting, and troubleshooting in complex Linux-based computing environments.
- Experience in worker scaling for training or inference workloads.
- Fundamental knowledge in ML models and how they run on GPUs.
Ownership and Collaboration
- Deep sense of ownership - proactively identifies opportunities, suggests improvements, and acts on them.
- The grit and adaptability to solve complex technical challenges that evolve day to day.
- Can explain technical concepts to both engineers and non-technical stakeholders
- Pushes for quality through constructive code review and collaboration
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent practical experience
## 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 recharge and explore.
🩺 Comprehensive health, vision, and dental coverage starting on day one.
💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join.
💻 Top-of-the-line tools and tech to fuel your creativity and productivity.
📍 Toronto HQ perks: Steps from Union Station and the PATH, with daily in-office lunches and dinners.
🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking.
🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey.
Key Responsibilities
- Build systems that power training and serving for generative AI models at scale
- Design distributed training infrastructure
- Optimize inference pipelines serving millions of users
- Focus on reliability, speed, and efficiency
- Deploy, support, and troubleshoot in complex Linux-based computing environments
- Manage worker scaling for training or inference workloads
Requirements
- Bachelor's degree in Computer Science
- Engineering
- related field
- or equivalent practical experience
Skills Required
KubernetesGCPLinuxGPU workloadsTPU workloadsDistributed systemsML modelsWorker scalingOwnershipCollaborationCommunicationProblem solvingAdaptabilityCode review
Benefits
- Competitive compensation
- Equity
- 4 weeks of vacation
- Comprehensive health, vision, and dental coverage
- RRSP/401(k) with employer match up to 4%
- Top-of-the-line tools and tech
- Daily in-office lunches and dinners
- Autonomy to explore and experiment
- Culture of learning and growth
- Mentorship
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