About the company
fal is the generative media ecosystem powering the next generation of AI products, building infrastructure, tools, and model access for developers and enterprises.
Responsibilities
- Work with the post-training team to extend SOTA image, video, audio, and 3D models with additional capabilities and modalities
- Develop novel approaches to model conditioning, generation, and editing, including training-free methods and model fine-tuning
- Leverage a massive GPU fleet to fine-tune generative models and build fine-tuning APIs
- Identify common patterns across models and develop reusable components, abstractions, and building blocks
- Apply state-of-the-art inference techniques to ensure models run efficiently with low latency and high throughput
- Build, deploy, and maintain scalable, reliable generative model APIs
- Work directly with customers to develop novel solutions to their generative media needs
Requirements
- 3+ years of professional experience as an Applied ML Engineer, with 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, Diffusers, and related tooling
- Ability to anticipate and solve challenges when deploying ML models to production
- Experience designing and implementing training-free extensions to generative models
- Experience developing custom post-training or fine-tuning approaches
- Track record of working in fast-paced startup environments
- Demonstrated ability to independently take ambitious ML ideas from concept to production
Conditions
- Interesting and challenging work
- Learning and growth opportunities
- Health, dental, and vision insurance (US)
- Regular team events and offsites
- Compensation: $180,000 - $230,000 + equity + comprehensive benefits package