Senior ML Engineer (Token Factory)
Tasks
- Build low precision inference pipelines
- Build low precision training pipelines
- Design inference engines
- Develop custom GPU kernels
- Develop distributed inference systems
- Develop distributed training systems
- Implement sharding strategies
- Implement speculative decoding
- Optimize hardware performance
- Optimize inference performance
- Optimize kv cache
- Profile GPU workloads
- Set up CI/CD pipelines
- Write unit tests
Perks/Benefits
- Career development
- Collaborative engineering culture
- Continuous learning
- Flexible work environment
- High autonomy
- International team
Skills/Tech-stack
Attention Mechanism | CI/CD | CUDA | Custom Kernels | Deep learning | Distributed Training | Distributed inference | FP8 | Flash Attention | GPU Profiling | Inference Optimization | KV cache | Language Models | Large Language Models | Low Precision | Low-precision inference | Low-precision training | MXFP4 | Machine Learning | Nsight | Precision Inference | PyTorch | PyTorch Profiler | Python | Quantization | Rotary Positional Embedding | Sharding | Speculative decoding | Training pipelines | Transformer | Unit Testing | Version control
Education
N/A
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