Software Engineer, Applied Machine Learning

Responsibilities

• Extend image, video, audio, and 3D generative models with new capabilities and modalities using conditioning, generation, editing, training-free methods, and fine-tuning.
• Develop and maintain fine-tuning APIs that let customers customize generative models.
• Create reusable model components, abstractions, building blocks, and inference pipelines.
• Optimize model inference for low latency, high throughput, and efficient GPU utilization.
• Build, deploy, and maintain scalable and reliable generative model APIs in production.
• Anticipate and resolve production challenges involving scalability, reliability, security, safety, and performance.
• Collaborate directly with customers to develop novel generative media solutions.

Requirements

• 3+ years of professional experience as an Applied ML Engineer, including at least 1–2 years focused on generative media or computer vision.
• Expert-level proficiency in Python and PyTorch.
• Deep practical understanding of diffusion and flow-based generative models.
• Hands-on experience with open-weight model ecosystems, including Hugging Face and Diffusers.
• Experience designing and implementing training-free extensions for image, video, audio, or 3D generative models.
• Experience developing and executing custom post-training or fine-tuning approaches for generative models.
• Ability to independently take ambitious machine learning ideas from concept to production.
• Experience in fast-paced startup environments or digital media and entertainment industries is valued.

Benefits

• Health, dental, and vision insurance in the US.
• Regular team events and offsites.
• Interesting and challenging work with learning and growth opportunities.