Machine Learning Engineer
Description For Machine Learning Engineer
Ideogram is at the forefront of creative AI technology, with a mission to democratize creative expression through state-of-the-art AI tools. 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, who have previously spearheaded transformative AI projects at Google Brain, UC Berkeley, CMU, and the University of Toronto.
The role involves building and deploying cutting-edge machine learning models at scale, working on highly complex challenges that shape the future of the creative economy. You'll be implementing advanced ML foundations, from Transformers to Denoising Diffusion models, and working directly with some of the best machine learning experts globally.
The company operates as a single flat team that transcends traditional roles, fostering a collaborative culture where everyone contributes to the company's and customers' success. Ideogram is committed to inclusivity and diversity, welcoming everyone regardless of their background. They provide strong mentorship and support for professional growth, believing that a small, dedicated team can move faster and build better products than large hierarchical organizations.
The founding team's track record includes groundbreaking projects like Imagen (Google's text-to-image system), Imagen Video, and fundamental work in Denoising Diffusion Models. Based in downtown Toronto with a presence in NYC, Ideogram offers an opportunity to work at the cutting edge of AI technology while contributing to making creative tools more accessible to everyone.
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
Requirements For Machine Learning Engineer
- 2+ 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
- Nice to have: Familiarity with kubernetes and docker
- Optional: Experience in low-level machine learning optimization, e.g., writing CUDA kernel code
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