AI Software Engineer
Tasks
- Customize inference frameworks for production requirements
- Design inference serving systems for large scale transformer and multimodal models
- Drive technical design and inference engineering best practices
- Implement and tune inference optimizations
- Monitor latency SLOs and respond to incidents
- Own end to end model deployment and serving API design
- Translate model architecture changes into inference efficient implementations
- Write and profile CUDA kernels and custom operations
Perks/Benefits
- Community involvement
- Health benefits
- Hybrid work options
- In-person work options
- Remote work options
- Wellbeing support
- Work-life balance
Skills/Tech-stack
C++ | CUDA | CUDA kernels | CUDA profiling | Cache Management | Continuous batching | FP8 | GPU Memory Optimization | GPU memory | INT4) | INT8 | KV cache | KV-cache management | Memory Optimization | Nsight | ONNX Runtime | Prefill Decode | Prefill decode disaggregation | Python | Quantization | SGLang | Speculative decoding | TensorRT-LLM | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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