AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Analyze serving pipeline bottlenecks
- Create testing datasets and deployment scenarios
- Design model serving architectures
- Develop benchmarking methodologies
- Improve inference infrastructure through experimentation
- Integrate inference solutions into production
- Monitor inference performance metrics
- Optimize inference frameworks and deployment strategies
- Optimize inference pipelines
- Run inference performance experiments
Perks/Benefits
- Collaborative international team
- Flexible location options
- Fully remote
- High technical ownership
- Professional development opportunities
Skills/Tech-stack
Benchmarking | Bottleneck analysis | Cloud Computing | Edge Computing | Inference Optimization | Inference frameworks | Latency optimization | Machine Learning | Memory Optimization | Model Deployment | Model Serving | Multi-Modal | Multi-modal Models | Performance Monitoring | Profiling | Resource-constrained computing | Scalability | Throughput Optimization
Education
N/A
Roles
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