Software Engineer, Applied Machine Learning

Sourced from theaiwins.com

fal is a generative media platform providing high-performance inference, orchestration, and model access for AI-native products. As an Applied Machine Learning Engineer, you will own the model layer of the generative media platform, bridging cutting-edge research and scalable production APIs. You will extend state-of-the-art open-source image, video, audio, and 3D models, build fine-tuning APIs, and optimize inference on a large GPU fleet.

• Extend SOTA image, video, audio, and 3D generative models with new capabilities and modalities
• Develop novel approaches to model conditioning, generation, and editing, including training-free methods and fine-tuning
• Build and maintain fine-tuning APIs for customer model customization
• Identify common patterns across served models and build reusable abstractions and building blocks
• Collaborate with the ML Performance & Optimization team on inference optimization for low latency and high GPU utilization
• Build, deploy, and maintain scalable, reliable generative model APIs
• Work directly with customers to develop novel generative media solutions

• 3+ years of professional experience as an Applied ML Engineer
• 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 such as Hugging Face and Diffusers
• Strong engineering judgment for scalable, reliable, secure, and performant production systems

• Experience designing training-free extensions to image, video, audio, or 3D generative models
• Experience with custom post-training or fine-tuning approaches
• Track record in fast-paced startup environments or digital media and entertainment
• Demonstrated ability to independently take ML ideas from concept to production