Seeking passionate Machine Learning Engineers to join the Inference team focusing on generative AI models and inference optimization for multi-modal generative models.

Company: Stability AI

Role: Generative AI Inference Engineer

Location: United States | Remote

Experience:

7+ years working on productionizing machine learning systems including inference pipeline development
5+ years working on python scientific stack, pyTorch and at least one high-performance inference framework
Experience profiling and optimizing deep neural networks on Nvidia GPUs
Experience deploying to cloud orchestration systems such as Kubernetes and cloud providers such as AWS, GCP, and Azure

Key Skills:

python services at scale
pyTorch
high-performance inference frameworks (e.g. Triton, TensorRT)
Diffusion Architecture
NVIDIA Nsight profiling tools
OpenCV
Docker
cloud orchestration systems
AWS
GCP
Azure
HuggingFace
W&B

Role Focus:

Design and develop customer-facing multi-modal ML inference systems
Build inference systems for next generation models including optimization, model tuning, and deployment
Partner with cloud providers to deliver hosted Stability AI inference solutions
Drive business impact through machine learning as a strategic thought partner
Bring new Stability models and pipelines into existence
Prototype and productionize inference platform improvements and new features

Additional responsibilities:

Work alongside top researchers and engineers using high-performance computing resources
Rapidly prototype solutions and iterate with tight product deadlines
Strong communication, collaboration, and documentation

Nice to have:

Familiarity with workflow tools like ComfyUI
Experience with the open-source ML ecosystem

Other:

Equal opportunity employer with non-discrimination policy

Generative AI Inference Engineer

Skills Required

Description