Phiar (S18)
We are developing a revolutionary AI-powered augmented reality navigation software solution for driving, that works as a smartphone app as well as in-vehicle displays.

Senior/Lead Computer Vision Engineer

$0 - $00.00% - 0.00%

Palo alto, CA
Full-time
1+ years
About Phiar

We are developing a revolutionary AI-powered augmented reality vehicle navigation platform with advanced artificial intelligence ADAS functionalities, powered by our ultra-lightweight road understanding AI that runs completely at-the-edge, in real-time, on just a smartphone level compute.

About the role

Skills: C++, Git, Python, Machine Learning, Computer Vision

Senior/Lead Computer Vision Engineer

Job Type: Full-Time Employer: Phiar Technologies, Inc. Location: Palo Alto, CA Link: http://www.phiar.net Contact: [email protected]

Company Description:

At Phiar, we combine cutting-edge innovation techniques in deep learning Artificial Intelligence (AI) and Augmented Reality (AR) to create a new vehicle navigation system which will promote safer driving, make routing more intuitive and better connect drivers with their surrounding environment.

We are a young startup based in Palo Alto, CA. Our team members have PhDs in Computer Vision, MS in Statistics and extensive experience in deep learning and data analytics research from Harvard and Columbia. We also have leaders with 10+ years of industry software and graphics development experiences. To round out our team, we have Professors in Computer Vision & Graphics and Cognitive Science as parts of our advisory board.

We are seeking a talented computer vision engineer as a key hire to our young team. The candidate should have experiences with classical and deep learning computer vision techniques in object recognition, semantic segmentation, or 3D scene reconstruction and/or SLAM. Knowledge and experiences in statistical machine learning and optimization is a plus. The ideal candidate should also be a versatile software hacker who is an excellent problem solver, and is able to deliver within schedule.

Requirements:

Minimum Qualifications MS in Computer Science or related field, with a focus in Computer Vision Familiar with OpenCV, and able to write clean code in Python and/or C/C++ with it Working knowledge in one of the popular deep learning frameworks (i.e. Torch, PyTorch, Keras, Caffe/Caffe2, Tensorflow)

Proficient in two of the following topics:

  • Object Detection and Localization
  • Object Tracking
  • Semantic Segmentation
  • SVM, Random Forests, Ensemble Models, Clustering, Boosting, and other supervised ML
  • Sampling Methods, optimization, graphical models, and statistical machine learning

Proficient in at least one of the following 3D computer vision areas:

  • 2D/3D object/scene reconstruction without depth sensor information
  • Monocular and/or stereo depth estimation & 3D geometry
  • Monocular SLAM and/or visual inertial odometry
  • Optic Flow Estimation
  • Depth and surface normal estimation and 3D geometry
  • Camera pose estimation and calibration

Preferred Qualifications

PhD in Computer Science, with focus on Computer Vision and/or Deep Learning

Expert in at least two of the CV/ML topics above, with peer-reviewed publications in the following top-tier venues: CVPR, ICCV, ECCV, ICLR, NIPS, PAMI

Bonus Points Experience working with CUDA, OpenGL, and/or OpenCL

Technology

iOS (Swift & Objective C), Git, openCV, openCL, openGL, Metal shader language, Python, JAVA, Android, TensorFlow, Vulkan.

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