Generative AI Inference Engineer
Stability AI
- Location
- United States
- Workplace
- Remote
- Employment
- Full Time
- Salary
- —
Posted 2mo ago
The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.
Responsibilities
- Lead design and development of customer-facing multi-modal ML inference systems
- Build inference systems for next-generation models (optimization, tuning, deployment)
- Partner with cloud providers for hosted Stability AI inference solutions
- Be a strategic thought partner on driving business impact through ML
- Bring new Stability models and pipelines into existence
- Prototype and productionize inference platform improvements and new features
Requirements
- 7+ years of productionizing machine learning systems, including inference pipeline development
- Expert level knowledge on writing and running python services at scale
- 5+ years working on python scientific stack, pyTorch
- 5+ years working on at least one high-performance inference framework (e.g. Triton and TensorRT)
- Deep understanding of Diffusion Architecture
- Experience profiling and optimizing deep neural networks on Nvidia GPUs, using profiling tools such as NVIDIA Nsight
- Experience with python-based image manipulation/encoding/decoding frameworks, such as OpenCV
- Experience deploying to cloud orchestration systems such as Kubernetes
- Experience deploying to cloud providers such as AWS, GCP, and Azure
- Experience with Docker
- Ability to rapidly prototype solutions and iterate on them with tight product deadlines
- Experience with the open-source ML ecosystem (HuggingFace, W&B, etc.)
Preferred
- Familiarity with workflow tools like ComfyUI
Skills
- Python
- PyTorch
- Triton
- TensorRT
- Nvidia GPUs
- NVIDIA Nsight
- OpenCV
- Kubernetes
- AWS
- GCP
- Azure
- Docker
- HuggingFace
- W&B
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