Principal Machine Learning Engineer, Mobile AI Inference Optimization
Tasks
- Build optimization pipeline
- Define mobile inference strategy
- Define on device benchmarking methodology
- Design scalable multi modal inference systems
- Drive model compression and quantization
- Establish code review standards
- Implement dynamic resolution and token reduction
- Implement inference runtimes adoption
- Lead and mentor ML engineers
- Partner with platform and runtime teams
- Set model deployment roadmap
- Track KPIs for latency accuracy memory power
- Translate research models to production
- Tune kernels for NPU GPU CPU
Perks/Benefits
- Commute subsidy
- Employee assistance program
- Employee resource groups
- Employee stock ownership
- Generous vacation and personal days
- Mental health programs
- Office Food Snacks
- Parental leave
- Retirement pension plans
- Training and development programs
- Volunteering and donation matching program
Skills/Tech-stack
ARM Mali | Android | Apple Neural Engine | C++ | CoreML | Deep learning | Diffusion Models | Executorch | FP16 | Generative Models | INT4 Quantization | IOS | Int8 Quantization | Knowledge Distillation | MLIR | Machine Learning | Memory layout | Metal | Model Compression | ONNX Runtime | Objective-C | OpenGL ES | Operator fusion | Pruning | Python | Qualcomm Adreno | Qualcomm Hexagon | Quantization | Runtime scheduling | Swift | TFLite | TVM | Transformers | Vulkan | XLA
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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