Research Engineer / Research Scientist (Post-training)

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, Character and Custom Models blog posts, and try Ideogram at ideogram.ai.

In this role, you will develop the post-training pipeline for our text-to-image foundation models end to end, from data strategy to deployment, advancing techniques such as RLHF, RLAIF, and work on personalization/customization. You will contribute to post-training research that drives measurable gains, and implement and maintain high-throughput fine-tune/eval pipelines. You'll work with a creative and ambitious team of engineers and researchers who are building the future of the creative economy.

• 5+ years of experience in developing machine learning models in JAX, PyTorch, or TensorFlow.

• Experience in implementing Machine Learning foundations (e.g., Transformer, VAE, Denoising Diffusion models) from scratch.

• Track record in machine learning innovation and familiarity with Deep Learning and advanced Machine Learning.

• End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI.

• Ability to debug machine learning models to iteratively improve model quality and performance.

• Nice to have: Familiarity with kubernetes and docker.

• Optional: Experience in low-level machine learning optimization, e.g., writing CUDA kernel code.

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.