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AI Specialist - Computational Photography
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Zurich, Switzerland
We are looking for a strong AI specialist with industry experience in developing and deploying machine learning (ML) computational photography algorithms that run in real-time on mobile or AR/VR platforms.
The mission of the Core AI Computational Photography team is to extract the highest imaging performance possible out of the physically-constrained cameras on AR and VR by developing device-optimized ML computational photography and computer vision algorithms. We also collaborate with the Family of Apps (Facebook, Instagram, WhatsApp, etc.) for enhancing photo and video quality at scale.
AI Specialist - Computational Photography Responsibilities
- Develop novel ML-based computational photography and image processing algorithms for AR and VR devices, particularly for ML-based denoising applications.
- Perform task-specific model optimization (particularly on model architecture) for on-device compute platforms
- Drive end-to-end (research to production) ownership of algorithm development
Minimum Qualifications
- 5+ years of industry experience with real-time (streaming video) ML-based computational photography algorithm development.
- 5+ years of industry experience with deploying ML computational photography algorithms on smartphones, AR/VR, or other compute and power constrained mobile devices.
- 5+ years of industry experience with ML image processing algorithms that tap in and out of on-device image signal processors (e.g. Qualcomm or MediaTek ISP)
- 4+ years of industry experience with CMOS sensor design and deep understanding of CMOS sensor mechanism and architecture.
- Strong understanding of mobile AI accelerators (e.g. Qualcomm HTP, DSP, GPU) and can articulate optimal neural network architecture design choices for such accelerators
- Strong understanding of engineering design tradeoffs for balancing image processing workloads on various SoC-based processors (e.g. what kind of workloads are best suited for CPU vs GPU vs DSP)
Preferred Qualifications
- Shipped ML computational photography features that have deployed commercially on camera-embedded devices, in particular ML-based denoising features.
- Published papers in computer vision or computational photography at top-tier conferences (CVPR, ECCV, ICCV, NeurIPS, etc.)
- Proficient in low-level device-side production languages such as C/C++, Halide, OpenGL/OpenCL, and Hexagon DSP programming.
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