Senior Machine Learning / Computer Vision Engineer

Glass Imaging is looking for a Senior Deep Learning / Computer Vision Algorithms Engineer, to work on advanced problems in computational photography. 

You would be responsible for bringing the latest cutting edge Computer Vision models into production on embedded devices and smartphones, from investigating, developing and training Deep Learning models and algorithms, to optimizing them for high throughput real time imaging applications.

Founded by former Apple Engineers who brought you Portrait Mode and other iPhone camera features, Glass is building the future of miniaturized imaging that delivers astonishing image quality and user experience. You’d be joining a unique team of creative and enthusiastic engineers with a passion and track record for revolutionizing the world of photography.

Required Skills & Experience:

• Strong Python skills + working knowledge of C/C++
• Expertise with Deep Learning implementations for imaging (UNet, Pix2Pix, GANs, CNN architectures, Image Transformers etc) with PyTorch or Tensorflow
• Model optimization & ML Ops experience - hyperparameter tuning, distributed training, building efficient data loaders & image preprocessing pipelines 
• Image processing, graphics & ML / Computer Vision algorithms, e.g.: Stereo Depth estimation, Guided/Bilateral filtering, feature matching, style transfer, iterative algorithms, BLAS; Libraries such as OpenCV; ISP (demosaic, denoise, HDR etc); 
• Computational photography methods. Inverse imaging: Super-resolution, deconvolution, inpainting. Knowledge of camera calibration, optics, lens design, color science, image quality
• Passion for keeping up to date with the latest AI research
• Excellent communication, analytical and problem solving skills, strong self motivation
• 3+ years of relevant Industry experience / MSc or PhD in a related technical field

Desired Experience: 

• Android or iOS development
• Embedded ML model optimizations: compression & sparsification, Neural Engines or converting models for dedicated AI hardware
• Embedded real-time algorithm implementations: GPU optimizations; general parallel programming techniques with e.g. OpenCL Vulkan, CUDA, Metal, OpenGL, SIMD, Assembly may be useful. Work with solutions tailored to Qualcomm Snapdragon GPUs/ISP/DSP. Knowledge of GPU Kernel performance tuning, profiling, cache usage, memory access patterns / architecture optimization
• Low level drivers, hardware interfaces, image sensors, FPGAs
• Published papers in relevant technical conferences (CVPR, ICCP, ICCV, NeurIPS etc).

We are a funded early-stage startup with great benefits (including stock options, competitive pay and health insurance), a small (but growing) and friendly team. We are all passionate about photography and hope you are too! We strongly prefer applicants based in or able to relocate to Bay Area, though remote may be possible in the right circumstances.