AI Research Engineer Intern (PhD), Real-Time Inference for Embodied AI
Tasks
- Balance model quality and runtime efficiency
- Build benchmarking pipelines for end to end performance
- Develop real time inference techniques for embodied AI
- Evaluate control frequency action latency system robustness
- Implement model compression quantization distillation
- Improve batching scheduling KV cache decoding
- Integrate optimized models into robot stacks and edge systems
- Optimize model latency throughput memory efficiency
- Perform graph compilation kernel level acceleration
Perks/Benefits
Skills/Tech-stack
Batching | CUDA | Decoding Optimization | Deep learning | GPU Performance | GPU Performance Optimization | Graph compilation | JAX | KV cache | Kernel optimization | Knowledge Distillation | Machine Learning | Model Compression | Model Inference | ONNX Runtime | Performance optimization | PyTorch | Quantization | Scheduling | TVM | TensorFlow | TensorRT | Triton | XLA
Education
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