Senior / Staff AI Research Engineer, Real-Time Inference
Tasks
- Apply structured sparsity for efficient inference
- Benchmark latency throughput power and accuracy
- Collaborate on model architectures for real time control loop latency
- Compile hardware aware inference graphs
- Deploy ML models to edge compute platforms
- Develop inference pipelines for embodied AI models
- Implement model compression including quantization pruning and distillation
- Optimize CUDA kernels and memory layout
- Profile and debug inference stacks
- Use TensorRT for performance optimization
- Use Triton for kernel optimization
Perks/Benefits
- 401k plan
- Dental insurance
- Equity program
- Fully stocked kitchen
- Green card support
- Health insurance
- Lunches Dinners In Office
- Stock options
- Team building events
- Visa sponsorship
- Vision insurance
Skills/Tech-stack
C++ | CUDA | CUDA kernels | Edge Computing | Embedded Systems | FP16 | GPU Architecture | Graph compilation | INT4) | INT8 | Knowledge Distillation | Layout optimization | Memory layout | Memory layout optimization | Model Compression | ONNX Runtime | Profiling | Pruning | Python | Quantization | Structured Sparsity | TVM | TensorRT | Triton
Education
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