Senior ML Engineer (Token Factory)
Tasks
- Apply attention and KV cache optimizations
- Build distributed training and inference systems
- Develop custom kernels
- Develop low precision training pipelines
- Implement inference engine components
- Improve throughput latency and cost per token
- Optimize LLM inference performance
- Profile and analyze GPU workloads
- Set up testing and CI CD for ML systems
Perks/Benefits
- Career development
- Collaborative engineering culture
- Continuous learning
- Flexible work environment
- High autonomy
- International team environment
Skills/Tech-stack
Attention Mechanism | CI/CD | CUDA | Custom Kernel | Distributed Training | FP8 | Flash Attention | GPU Optimization | KV cache | MXFP4 | Nsight | PyTorch | PyTorch Profiler | Python | Quantization | ROPE | Sharding | Speculative decoding | Transformer | Unit Testing | Version control
Education
N/A
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