Principal Engineer for On-Device AI Inference & Systems, owning the inference and integration stack end-to-end to make state-of-the-art multi-modal models run fast, small, and reliably within a browser-native runtime for game experiences.
Zone A: $250,300 - $325,400
Zone B: $222,600 - $289,400
Zone C: $197,400 - $256,600
- Own the end-to-end optimization pipeline: model export, graph transformation, operator fusion, memory-layout planning, and hardware-specific kernel tuning across NPU, mobile GPU, and desktop/laptop GPU.
- Make authoritative decisions on quantization (INT4/INT8/FP16), weight sharing, structured/unstructured pruning, and knowledge distillation to hit hard latency, memory, and power budgets.
- Drive low-level performance work: write and tune WebGPU compute shaders (WGSL) and, where relevant, native kernels (Metal, Vulkan/SPIR-V compute, D3D12, CUDA).
- Evaluate, select, and drive adoption of WebGPU-targeted inference runtimes (ONNX Runtime Web, Transformers.js, WebLLM, TensorFlow.js) alongside native options (CoreML, ONNX Runtime, TFLite, ExecuTorch).
- Design and own the integration between the ML runtime and the game engine: real-time scheduling, threading, memory pooling, zero-copy buffer sharing between the inference path and the render path, and frame-budget management alongside the renderer.
- Nice to have: World-model
- Nice to have: Neural-rendering