Develop and deploy deep learning models for medical imaging: prototype and production work, design and run experiments, document results, collaborate on data labeling, and optimize models for inference and deployment.
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 DescriptionThe 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.
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