Applied ML Engineer - Generative Media & Models Production

Speedrun Talent Network; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health/Dental/Vision

Team offsites

Growth opportunities

Job summary

fal is the generative media ecosystem powering the next generation of AI products. We are seeking a hands-on, production-focused Applied Machine Learning Engineer to take technical ownership of the model layer powering our next-generation generative media platform.

You will extend SOTA open-source models, fine-tune on our GPU fleet, and deploy scalable model APIs, collaborating with customers including large e-commerce retailers and film/TV studios.

Qualifications

• 3+ years of professional experience as an Applied ML Engineer, with at least 1–2 years focused on generative media or computer vision.
• Core frameworks: Python and PyTorch
• Deep understanding of diffusion and flow-based generative models
• Experience with open-weight model ecosystems (Hugging Face, Diffusers)
• Ability to deploy ML models to production with scalable, reliable systems

Responsibilities

• Develop novel model pipelines for image, video, audio, and 3D modalities.
• Fine-tune models on large GPU fleets and maintain fine-tuning APIs.
• Identify reusable components and abstractions to accelerate new model capabilities.
• Collaborate with ML Performance & Optimization to improve latency and throughput.
• Build, deploy, and maintain scalable generative model APIs for customers.
• Engage with customers to understand generative media needs and translate them into solutions

Skills

Python

PyTorch

Machine Learning

Production ML

Tools

Hugging Face

Diffusers

Job description

fal is the generative media ecosystem powering the next generation of AI products. We are seeking a hands-on, production-focused Applied Machine Learning Engineer to take technical ownership of the model layer powering our next-generation generative media platform.

You will extend SOTA open-source models, fine-tune on our GPU fleet, and deploy scalable model APIs, collaborating with customers including large e-commerce retailers and film/TV studios.