Software Engineer Applied Machine Learning

You will take technical ownership of the generative-model layer for a production platform. You will extend open-source image, video, audio, and 3D models; fine-tune models; build reusable inference components and fine-tuning APIs; optimize performance; deploy reliable APIs; and collaborate directly with customers on generative-media solutions.

Responsibilities

• Extend image, video, audio, and 3D models with new capabilities and modalities
• Develop model conditioning, generation, and editing approaches
• Fine-tune generative models and build fine-tuning APIs
• Develop reusable components and abstractions for model capabilities and inference pipelines
• Apply inference optimization techniques for latency, throughput, and GPU utilization
• Build, deploy, and maintain scalable generative model APIs
• Resolve production challenges to ensure reliable service at scale
• Collaborate with customers on generative media solutions

Requirements

• 3+ years of professional experience as an Applied ML Engineer
• 1–2 years focused on generative media or computer vision
• Expert proficiency in Python and PyTorch
• Practical understanding of diffusion and flow-based generative models
• Experience with Hugging Face, Diffusers, and open-weight model tooling
• Ability to deploy scalable, reliable, secure, safe, and performant ML systems
• Experience designing training-free extensions to generative models
• Experience with custom model post-training or fine-tuning
• Ability to take ML ideas from concept to production

Benefits

• Health, dental, and vision insurance in the US
• Regular team events and offsites
• Equity