AI Research Engineer
Tasks
- Apply batching optimization
- Apply model efficiency optimizations in cloud
- Apply model efficiency optimizations on device
- Build generative AI and LLM solutions
- Conduct structural and neural search
- Develop learning based optimization methods
- Develop long context techniques
- Develop machine learning algorithms
- Develop optimization based learning methods
- Develop speculative decoding
- Implement KV caching
- Implement efficient attention mechanisms
- Optimize generative AI inference
- Perform model compression
- Prototype generative AI systems
- Prototype with hardware in loop
- Research quantization algorithms
Perks/Benefits
- N/A
Skills/Tech-stack
Attention | Batching | Deep learning | Generative AI | Hardware-in-the-loop | KV cache | Language Models | Large Language Models | Machine Learning | Mixed Precision | Model Compression | Neural Search | PyTorch | Python | Quantization | Speculative decoding | Structural Search | The Loop
Education
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