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 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 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.

Requirements

Must-haves

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

Nice-to-haves

PhD degree in computer science, engineering, or mathematics
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
An outstanding start-up culture;
Transparent, collaborative work environment;
Competitive compensation
All your information will be kept confidential according to EEO guidelines.

Application prep

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Keywords to mirror

python

Platform: smartrecruiters
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k