ML Application Engineer – AI Inference & Model Optimization (Staff/Senior Staff level) - Riyadh, KSA
Tasks
- Align model requirements with system constraints
- Analyze inference trade offs accuracy vs efficiency
- Build and deploy scalable inference pipelines
- Convert and quantize models
- Design end-to-end AI pipelines
- Implement runtime optimization for inference
- Integrate ONNX into inference pipelines
- Lead hardware sizing and architecture discussions
- Optimize model throughput latency and accuracy
- Port deep learning models to AI accelerators
- Profile and debug model performance bottlenecks
- Provide customer facing technical guidance
- Validate model capability in deployment environments
Perks/Benefits
- Customer facing technical collaboration
- Technical documentation and training opportunities
- Travel for customer engagements
Skills/Tech-stack
C# | C++ | Containers | Debugging | Git | INT8 | Inference acceleration | Kubernetes | Latency optimization | Linux | Mixed Precision | Model Optimization | NVIDIA Triton | ONNX | ONNX Runtime | Profiling | PyTorch | Python | Quantization | TGI | TensorFlow | Throughput Optimization | VLLM
Education
Regions
Countries
States
Cities
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