AI Research Engineer (Kernel & Inference Optimization)
About the role
AI Research Engineer (Kernel & Inference Optimization) - 100% Remote Worldwide. Design and deploy model-serving architectures for high throughput, low latency, and lower memory use, including on resource-constrained and edge devices.
What you'll do
- Design and deploy model-serving architectures for high throughput, low latency, and lower memory use.
- Run those pipelines on resource-constrained devices and edge platforms.
- Establish performance targets and resolve production bottlenecks.
- Engineer inference pipelines that stay fast and small in real-world use.
Requirements
- A degree in Computer Science or a related field. A PhD in NLP or machine learning is ideal, with publications in top conferences.
- Must know Metal Shading Language and be comfortable writing custom compute shaders.
- Proven experience in low-level kernel optimization and inference optimization on mobile devices.
- Contributions should have produced measurable inference improvements.
About Tether
Tether builds reserve-backed digital tokens and hires research engineers to make model inference faster and smaller on constrained devices.
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