Machine Learning Engineer
Description For Machine Learning Engineer
Ideogram is revolutionizing the creative industry by developing AI-powered tools that make professional-quality design accessible to everyone. As a Machine Learning Engineer, you'll join a distinguished team led by world-renowned AI experts including Mohammad Norouzi, Jonathan Ho, William Chan, and Chitwan Saharia - the minds behind groundbreaking projects like Google's Imagen and Denoising Diffusion Models.
You'll be working on cutting-edge machine learning challenges, implementing and deploying state-of-the-art models at scale. The role requires deep expertise in machine learning foundations, including transformers, VAEs, and diffusion models. You'll be part of a flat, collaborative team structure that values quick iteration and innovation.
The company maintains headquarters in downtown Toronto with a growing presence in NYC, offering a unique opportunity to work with some of the best minds in AI. Ideogram's culture emphasizes mentorship, growth, and a commitment to inclusivity. They're building an AI-native application that helps creative individuals and teams produce high-quality content faster and more cost-effectively.
This position is perfect for experienced machine learning engineers who are passionate about pushing the boundaries of generative AI and want to make a significant impact in the creative economy. You'll be working on highly complex challenges while contributing to a product that's actively shaping the future of creative tools. The role offers the chance to work directly with industry leaders who have proven track records in executing transformative AI projects.
Responsibilities For Machine Learning Engineer
- Build and deploy state of the art machine learning models at scale
- Work with a creative and ambitious team of engineers and researchers
- Work directly with machine learning experts in building the future of the creative economy
Requirements For Machine Learning Engineer
- 5+ years of experience in developing machine learning models in JAX, PyTorch, or TensorFlow
- Experience in implementing Machine Learning foundations (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
- Ability to debug machine learning models to iteratively improve model quality and performance
- Familiarity with kubernetes and docker (nice to have)
- Experience in low-level machine learning optimization, e.g., writing CUDA kernel code (optional)
