We raised a $130M Series A — and we’re only getting started. This is your chance to join early, when the team is small but mighty, and help build the next GenAI decacorn.

What you will work on

Design and implement end-to-end training pipelines for state-of-the-art models in computer vision - video and image generative models.
Develop complex data pipelines to transform raw inputs (images, video, text, audio) into high-quality, annotated datasets that power model training and evaluation.
Work tightly with scrapping and annotation teams.
Optimize models for speed, scalability, and efficiency.
Develop tools and frameworks to accelerate training, evaluation, and deployment of large models.
Collaborate with product and design teams.
Beat other models on public benchmarks (e.g. LMArena, Artificial Analysis)

Your must haves

***(**You don’t need to meet every single requirement to be a strong candidate — if you’re excellent in a few of these areas and eager to grow, we’d still love to hear from you. )

Proven track record of training and deploying ML models into production (experience with large-scale vision (especially diffusion models), NLP, or multimodal systems is a big plus).
Strong skills in model training, optimization, and evaluation, with hands-on experience in distributed training and multi-GPU systems is a big plus.
Knowledge of modern ML research trends, frameworks, and tooling (e.g., PyTorch, Hugging Face, DeepSpeed, Accelerate, Ray).
Experience with evaluation of complex ML systems.
Willingness to work in a fast-paced, high-intensity startup environment.
Excellent communication skills and ability to collaborate across research, engineering, and product teams.