AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build scalable inference pipelines
- Conduct inference experiments
- Create testing datasets and deployment scenarios
- Design model serving architectures
- Develop benchmarking methodologies
- Identify inference bottlenecks
- Improve inference infrastructure through experimentation
- Integrate inference solutions into production
- Monitor performance metrics
- Optimize inference frameworks and deployment strategies
Perks/Benefits
- Autonomy and creativity
- Collaborative international team
- Continuous learning and professional development
- Flexible location options
- Fully remote work environment
- Technical ownership and influence
Skills/Tech-stack
Artificial Intelligence | Benchmarking | Cloud Computing | Data Pipelines | Edge Computing | Error Analysis | Inference Optimization | Inference frameworks | Latency optimization | Machine Learning | Memory Optimization | Model Serving | Multimodal Models | Network Overhead Analysis | Overhead Analysis | Performance Monitoring | Profiling | Programming Languages | Resource-constrained systems | Response time | Scalability | Throughput Optimization | Token Response Time
Education
N/A
Roles
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