About the postition
As a Model Development Engineer at MVNT, you will build and optimize the AI models that power our dance generation platform. You will translate cutting-edge research into production-ready systems, focusing on generative AI models for human motion synthesis. Working closely with our research team, you will develop scalable training pipelines, optimize model architectures, and deploy AI systems that create culturally authentic dance content for gaming and entertainment applications.
In this role, you will:
Develop and implement generative AI models for dance motion synthesis using diffusion models, autoregressive architectures, and other state-of-the-art approaches
Build robust training pipelines for skeletal animation and human pose data processing
Optimize model performance, inference speed, and memory efficiency for production deployment
Collaborate with researchers to translate academic breakthroughs into scalable engineering solutions
Design and maintain data preprocessing pipelines for 3D motion capture and 2D pose estimation datasets
We'll be perfect if you have:
2+ years of experience in machine learning engineering or model development
Strong proficiency in Python, PyTorch, and modern ML frameworks
Hands-on experience with generative AI models (diffusion models, GANs, autoregressive models, VAEs)
Understanding of human pose estimation, skeletal animation, or 3D computer vision
Experience with model training, hyperparameter optimization, and MLOps practices