Senior/Lead Computer Vision Engineer
Job Type: Full-Time
Employer: Phiar Technologies, Inc.
Location: Palo Alto, CA
Link: http://www.phiar.net
Contact: chenping.yu@phiar.net
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
Phiar
