Software Engineer, ML Infrastructure at Ideogram — AI Jobs | Neura Market
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    Ideogram

    Software Engineer, ML Infrastructure

    Ideogram

    Toronto

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    Full-time
    On-site
    7/9/2026
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    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.

    Try Ideogram at ideogram.ai, and check out the following links to learn more about our work: Ideogram 4.0, Enterprise, and Custom Models.

    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.

    Tasks

    • •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.

    Perks & Benefits

    EquityDental insuranceVision insuranceMentorship

    Skills & Tech Stack

    KubernetesGCPDiffusion Models

    Education

    Bachelor's DegreeComputer Science

    Roles

    Software EngineerEngineer

    Location

    Region

    North America

    Country

    Canada

    City

    Toronto

    Topics

    Engineering

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