Senior ML Engineer (Token Factory)
Tasks
- Collaborate on distributed training systems
- Design inference engines
- Develop custom GPU kernels
- Develop low precision inference pipelines
- Develop low precision training pipelines
- Implement sharding strategies
- Implement speculative decoding
- Improve hardware aware optimizations
- Improve throughput and reduce latency
- Optimize LLM inference performance
- Optimize kv cache
- Profile and analyze GPU workloads
- Set up testing and CI CD for ML systems
Perks/Benefits
- Career development
- Collaborative engineering culture
- Continuous learning opportunities
- Flexible work environment
- High autonomy and ownership
- International diverse team environment
Skills/Tech-stack
Attention Mechanism | CI/CD | CUDA | Custom Kernels | Distributed Training | FP8 | Flash Attention | GPU Profiling | Inference engine | KV cache | Language Models | Large Language Models | Low Precision | Low-precision training | MXFP4 | Machine Learning | Nsight | PyTorch Profiler | Python | Quantization | ROPE | Sharding | Speculative decoding | Transformer | Unit Testing | Version control
Education
N/A
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