Machine Learning Engineer

Goal: Turn cutting-edge research into production systems that generate professional-grade creative content.

You will:

• Scale models from “cool demo” to assets used in real ads, films, and design work.
• Chase small wins that matter (a 0.01% improvement can be the line between amateur and pro).
• Build multi-stage inference pipelines for video, text, images, audio, and 3D – with real-time feedback and human-in-the-loop refinement.
• Serve large multimodal models with sub-second latency and progressive rendering.
• Apply quantization, distributed serving, and memory optimizations to run at a billion-request scale.

Candidate Background:

• Deep knowledge of modern deep learning architectures, optimization, and tooling.
• Proficiency in PyTorch or JAX.
• Experience designing, training, and evaluating deep learning systems.
• Breadth across ML literature (beyond just generative models).