Senior ML Engineer (Token Factory)
Tasks
- Build distributed training and inference systems
- Design inference engines
- Develop custom GPU kernels
- Develop low precision training and inference pipelines
- Implement sharding strategies
- Implement speculative decoding
- Improve production ML system maintainability
- Optimize GPU memory and compute trade offs
- Optimize LLM inference performance
- Optimize kv cache
- Profile GPU workloads
- Set up testing and CI/CD
Perks/Benefits
- Career development
- Collaborative innovation culture
- Continuous learning
- Diverse team environment
- Flexible work environment
- High autonomy
- International team
Skills/Tech-stack
Attention Mechanisms | CI/CD | CUDA | Custom Kernels | Distributed Training | FP8 | Flash Attention | GPU Architecture | GPU Profiling | Inference Optimization | KV cache | Language Models | Large Language Models | MXFP4 | Machine Learning | NVIDIA Nsight | PyTorch | PyTorch Profiler | Python | Quantization | ROPE | Sharding | Speculative decoding | Transformer | Unit Testing | Version control
Education
N/A
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