Senior ML Engineer (Token Factory)
Tasks
- Analyze GPU performance constraints
- Apply sharding strategies
- Build distributed inference systems
- Build distributed training systems
- Design inference engines
- Develop custom GPU kernels
- Develop low precision inference pipelines
- Develop low precision training pipelines
- Establish ML testing best practices
- Implement CI/CD pipelines
- Implement hardware-aware optimizations
- Implement speculative decoding
- Maintain production grade ML systems
- Optimize LLM inference performance
- Optimize kv cache
- Profile GPU workloads
- Support dense models and MoE models
Perks/Benefits
- Career development
- Collaborative innovation driven culture
- Continuous learning
- Flexible work environment
- High autonomy
- International diverse team
Skills/Tech-stack
Attention Mechanism | CUDA | Custom Kernels | Distributed Training | FP8 | Flash Attention | GPU Profiling | KV cache | Language Model | Large Language Model | MXFP4 | Machine Learning | Memory hierarchy | Nsight | PyTorch | PyTorch Profiler | Python | Quantization | ROPE | Sharding | Speculative decoding | Transformer
Education
N/A
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