Software Engineer, Applied Machine Learning

About the job

Responsibilities

• Extend state-of-the-art image, video, audio, and 3D models with additional capabilities and modalities, developing novel approaches to model conditioning, generation, and editing.
• Fine-tune generative models for novel capabilities using a large GPU fleet and build/maintain fine-tuning APIs for customer customization.
• Identify common patterns across models and develop reusable components, abstractions, and building blocks to accelerate development of new model capabilities and inference pipelines.
• Apply state-of-the-art inference techniques and best practices to ensure efficient model performance with low latency, high throughput, and optimal GPU utilization.
• Build, deploy, and maintain scalable, reliable generative model APIs, anticipating and resolving production challenges.
• Collaborate directly with customers, including large e-commerce retailers and film/TV studios, to develop novel generative media solutions.

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 working with open-weight model ecosystems like Hugging Face and Diffusers.
• Ability to anticipate and solve challenges in deploying ML models to production, with strong engineering judgment for scalable, reliable, secure, safe, and performant systems.
• Experience designing and implementing training-free extensions to generative models.
• Experience developing and executing custom post-training or fine-tuning approaches for generative models.
• Demonstrated ability to independently take ambitious ML ideas from concept to production.

Benefits

• Health, dental, and vision insurance (US)
• Regular team events and offsites
• Equity
• Comprehensive benefits package