Machine Learning Engineer

Company Description

Founded in 2016, VoxelCloud, Inc. is a Los Angeles-based worldwide leader in AI analysis of medical images. Backed by Sequoia and Tencent. We help healthcare providers make better/earlier diagnoses and related clinical decisions, improving outcomes for all. http://www.voxelcloud.ai

Job Description

The R&D team (located in Los Angeles, CA) is involved with research and development of innovative solutions to medical imaging applications, including disease detection/quantification in medical scans, disease risk stratification, image synthesis, text report mining, and more! We are currently hiring both full-time and interns to join our R&D team.

Responsibilities:

• Develop deep learning models for prototyping and production purposes according to product feature request

• Design, implement and test model experiments using major deep learning frameworks

• Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)

• Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling

• Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed

• Conduct methodology research in deep learning to drive scalable, real-time implementation

Qualifications

Basic Qualifications

• MS degree in computer science, engineering, or mathematics

• 2-3 years of relevant experience in building deep learning solutions for computer vision problems

• Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch

• Proficient in Python

• Good CS fundamentals in data structures and algorithm

• Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged

• Work well in teams and communicate ideas clearly

Preferred Qualifications

• PhD degree in computer science, engineering, or mathematics

• 3-5 years of relevant experience in building deep learning solutions for computer vision problems

• Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).

• Track record of publications in CV and medical image analysis is a plus

• Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus

• Prior experience with medial images is a plus​​​​​​

Additional Information

We Offer…

• An outstanding start-up culture;

• Transparent, collaborative work environment;

• Competitive compensation

• Excellent Medical, Dental, and Vision coverage

• 401k, paid Vacation and Holiday

All your information will be kept confidential according to EEO guidelines.