Senior Machine Learning Engineer

About the role

Join Genies, a leading avatar technology company, as a Senior Machine Learning Engineer. In this role, you will develop core machine learning models for animation generation, explore modern generative architectures, and drive the full ML lifecycle. You will collaborate with various teams and optimize models for performance. Enjoy a flexible work environment, comprehensive health insurance, competitive salaries, and a vibrant office space. Key missions: Design, train, and deploy machine learning models for animation generation, including text-to-motion, audio-driven facial animation, and full-body performance systems.. Explore and implement modern generative architectures, including diffusion models, transformers, and hybrid approaches for motion synthesis.. Drive the full ML lifecycle, including data processing, training, evaluation, optimization, and deployment. Profile: - You are self-directed and comfortable working on open-ended problems - You communicate clearly and collaborate effectively across ML, engineering, and content teams - Familiarity with model optimization and deployment techniques (e.g., ONNX, real-time inference) is a plus - Hands-on experience with generative models such as diffusion, transformers, VAEs, or GANs - 7+ years of experience in machine learning, with a focus on generative models, multimodal systems, or related areas - Experience owning end-to-end ML systems, from research through production deployment - You are comfortable working at the intersection of research and production - You think in terms of systems, not just models, and understand how ML fits into larger product pipelines - Background in 3D animation systems, motion data, or computer graphics is strongly preferred - Experience building and training models using frameworks such as PyTorch - Experience working with multimodal data (e.g., text, audio, video, or motion) - You have strong intuition for model design and understand the tradeoffs between different architectures - Strong foundation in machine learning fundamentals, including probability, optimization, and deep learning architectures