AI/ML performance engineer
INR 1500K-2100K (estimate) Mid-level Full Time
Tasks
- Analyze AI workload performance
- Analyze NoC DMA and SMMU bottlenecks
- Apply quantization pruning and mixed precision
- Benchmark and optimize neural network models
- Build benchmarks micro benchmarks and profilers
- Collaborate on drivers runtimes compilers and frameworks performance
- Identify compute memory bandwidth bottlenecks
- Optimize AI inference latency
- Optimize AI power efficiency
- Optimize AI throughput
- Optimize operator fusion and graph partitioning
- Perform roofline utilization and memory access analysis
Perks/Benefits
- N/A
Skills/Tech-stack
Android | Bandwidth analysis | Batching | Benchmarking | DMA | Deep learning | Graph partitioning | Hardware performance | Hardware performance counters | Linux | Machine Learning | Memory bandwidth | Memory bandwidth analysis | Mixed Precision | Model Quantization | NOC | Network Pruning | Neural Network | Neural Networks | Neural network pruning | Operator fusion | Performance counters | Profiling | RTOS | Roofline analysis | SMMU | Tiling | Virtualization
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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