Applied Machine Learning

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 , and check out the following links to learn more about our work: Ideogram 4.5, Enterprise, and Custom Models.

The Opportunity

As an Applied ML Engineer at Ideogram, you’ll bridge research and product – turning frontier generative models into production features across our first-party app and API. You’ll experiment quickly, build rigorous evaluations and datasets, and partner with research, engineering, infra, while working directly/frequently with clients to ship reliable and scalable ML systems. You’ll fine-tune and deploy models for creative use cases (text-to-image, image-to-text, image enhancement and editing, multimodal), set clear client success metrics (quality, latency, cost), and contribute to safety, monitoring, and reliability of systems. You’ll lead 0 to 1 projects that shape Applied ML enterprise practices at Ideogram, while delivering features that create delight and real value for our users.

What We’re Looking For

• 1+ years of building and shipping ML products

• You write backend code in Python/ PyTorch/ Jax

• You design benchmarks and evaluation metrics, run error analyses, and debug numerical stability across data, training, and inference

• You’ve taken ML features from idea to evaluation to production with measurable gains (quality, latency, or cost)

• You collaborate with the product team to define success criteria and iterate quickly and pragmatically

• You’re comfortable curating, labeling, and cleaning datasets, and designing evaluation corpora and failure-mode analyses

• You’re familiar with modern deep learning such as transformers, diffusion, and encoders

• You bring ownership, urgency, curiosity, and learn fast in a startup setting

• Strong communication and interpersonal skills

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.