AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build scalable inference pipelines
- Create testing datasets and deployment scenarios
- Design model serving architectures
- Develop benchmarking methodologies
- Experiment to improve inference infrastructure
- Improve memory utilization
- Integrate optimized inference solutions into production
- Monitor performance metrics
- Optimize inference frameworks and deployment strategies
- Optimize inference latency and throughput
- Profile and identify serving bottlenecks
- Run inference experiments in simulated and production environments
Perks/Benefits
- Autonomy and technical ownership
- Continuous learning and professional development
- Flexible location options
- Fully remote work
- International team collaboration
Skills/Tech-stack
Benchmarking | CUDA | Docker | Inference Optimization | Kubernetes | Latency optimization | Linux | Memory Optimization | Model Serving | ONNX | Performance Monitoring | Profiling | PyTorch | Python | TensorFlow | Throughput Optimization | Tokenization
Education
N/A
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