AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build inference pipelines across cloud edge and resource constrained environments
- Create benchmarking methodologies and performance validation
- Create testing datasets and deployment scenarios
- Design model serving architectures
- Identify serving pipeline bottlenecks
- Improve inference infrastructure through experimentation and iteration
- Integrate optimized inference into production
- Monitor inference metrics
- Optimize inference frameworks and deployment strategies
- Optimize inference latency and throughput
- Run inference experiments and evaluate performance
Perks/Benefits
- Autonomy and creativity
- Collaborative international team
- Continuous learning and professional development
- Flexible location options
- Fully remote work
- Technical ownership
Skills/Tech-stack
AI Model Deployment | AI model | Artificial Intelligence | Benchmarking | Bottleneck analysis | Cloud Computing | Edge Computing | Inference Optimization | Latency optimization | Machine Learning | Memory Optimization | Model Deployment | Model Serving | Multi-Modal | Multi-modal Models | Performance Monitoring | Profiling | Resource constraints | Scalability | Throughput Optimization
Education
N/A
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