AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Analyze serving pipeline bottlenecks
- Build scalable inference pipelines
- Create testing datasets and deployment scenarios
- Design model serving architectures
- Develop benchmarking methodologies
- Improve inference infrastructure through experimentation and iteration
- Integrate inference solutions into production environments
- Monitor performance metrics
- Optimize inference frameworks and deployment strategies
- Run inference experiments in simulated and production environments
Perks/Benefits
- Autonomy and creativity
- Continuous learning and professional development
- Flexible location options
- Fully remote work
- Innovation-driven culture
- International collaborative team
- Technical ownership and influence
Skills/Tech-stack
AI Systems Performance | AI systems | 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 hardware | Systems performance | Throughput Optimization
Education
N/A
Roles
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