AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build scalable inference pipelines for cloud edge constrained environments
- Collaborate to integrate optimized inference solutions into production
- Conduct inference performance experiments and evaluate reliability
- Create testing datasets and deployment scenarios for real world challenges
- Design optimize model serving architectures for low latency high throughput
- Develop benchmarking methodologies and performance validation frameworks
- Identify bottlenecks in serving pipelines batch network memory
- Improve inference infrastructure through experimentation iteration adoption
- Monitor and analyze latency throughput memory error metrics
- Optimize inference frameworks and deployment strategies
Perks/Benefits
Skills/Tech-stack
Artificial Intelligence | Benchmarking | Bottleneck analysis | Inference Optimization | Inference scalability | Latency optimization | Machine Learning | Memory Optimization | Model Deployment | Model Serving | Multi-Modal | Multi-modal Models | Network Overhead | Performance Monitoring | Performance Profiling | Profiling | Response time | Throughput Optimization | Token Response Time
Education
N/A
Roles
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