Research Engineer / Research Scientis (Post-training)

About

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.

Requirements

• End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI
• Track record in machine learning innovation and familiarity with Deep Learning and advanced Machine Learning
• 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
• Ability to debug machine learning models to iteratively improve model quality and performance

Nice to have

• Familiarity with kubernetes and docker
• Experience in low-level machine learning optimization, e.g., writing CUDA kernel code