Machine Learning Engineer

Ideogram (Headquarters: Toronto / NYC)

AI Machine Learning Deep Learning Generative AI Diffusion Models Python PyTorch TensorFlow Computer Vision Startup Creativity Tools AI Engineer

Company: Ideogram
Location: NYC or Toronto (Onsite)
Type: Full-time

Company Description:
Ideogram’s mission is to help people become more creative. Our thesis is that everyone has an innate desire to create. We are developing state-of-the-art AI tools that will make creative expression more accessible and efficient. We are pushing the limits of what’s possible with AI, with a focus on creativity and a high standard for trust and safety. Our headquarters is in downtown Toronto, and we have a small presence in NYC. We recently launched Ideogram 3.0, featuring advancements in image-prompt alignment, photorealism, and text rendering, along with Ideogram Canvas for infinite creative editing with tools like Magic Fill and Extend. Our founding team consists of world-renowned AI experts from Google Brain, UC Berkeley, CMU, and the University of Toronto, responsible for foundational work like Imagen and Denoising Diffusion Models.

Role Description:
We are seeking talented Machine Learning Engineers to join our team and contribute to developing the next generation of generative AI models for creativity. You will work on challenging problems at the forefront of AI research, pushing the limits of text-to-image generation, image editing, and multimodal understanding. Responsibilities include designing, implementing, and training large-scale deep learning models, improving model performance (realism, prompt adherence, text rendering), and collaborating with researchers and engineers to bring cutting-edge AI capabilities into our products like Ideogram 3.0 and Canvas.

Responsibilities:
*   Design, train, and evaluate state-of-the-art generative models (e.g., diffusion models).
*   Develop and implement novel ML techniques to improve image quality, style consistency, and controllability.
*   Work with large datasets and distributed training infrastructure.
*   Collaborate with the research team to translate ideas into production-ready models.
*   Optimize models for inference speed and efficiency.
*   Stay up-to-date with the latest advancements in generative AI and deep learning.

Ideal Candidate:
*   Strong background in Machine Learning, Deep Learning, and specifically Generative Models (Diffusion Models, GANs, VAEs).
*   Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
*   Experience with large-scale model training and distributed computing.
*   Solid understanding of computer vision concepts.
*   Published research in top-tier ML/AI conferences (NeurIPS, ICML, CVPR, etc.) is a plus.
*   Passion for creativity and building tools that empower users.
*   Ability to work collaboratively in a fast-paced startup environment.
*   M.S. or Ph.D. in Computer Science, AI, or a related field, or equivalent practical experience.