18 hours ago
Base Salary
$180k - $230k/yr
Responsibilities
- Extend image, video, audio, and 3D generative models with new capabilities and modalities using conditioning, generation, editing, training-free methods, and fine-tuning.
- Fine-tune generative models and build APIs that allow customers to customize models.
- Develop reusable components, abstractions, and building blocks for model capabilities and inference pipelines.
- Optimize inference for low latency, high throughput, and efficient GPU utilization.
- Build, deploy, and maintain scalable and reliable generative model APIs.
- Collaborate directly with customers to develop solutions for generative media use cases.
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 training-free extensions for image, video, audio, or 3D generative models.
- Experience developing custom model post-training or fine-tuning approaches.
- Ability to design scalable, reliable, secure, safe, and performant production ML systems.
- Startup or digital media and entertainment industry experience is a nice-to-have.
- Demonstrated ability to independently take ambitious ML ideas from concept to production.
Benefits
- Health, dental, and vision insurance in the US.
- Regular team events and offsites.
- Interesting and challenging work with learning and growth opportunities.
- Compensation includes $180,000–$230,000 base salary plus equity and comprehensive benefits.
Categories
About fal
Fal builds a generative media platform that gives developers a unified API to run state-of-the-art image, video, and audio models. It provides serverless GPUs, high-performance inference, and dedicated compute clusters so teams can customize, deploy, and scale models in production. The company is privately held and headquartered in San Francisco, serving both startups and enterprises through a commercial API and managed infrastructure.