Machine Learning Engineer - Computer Vision & NLP

Los angelesCaUs
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**Company: Voxelcloud **

Job Description The R&D team (located in Los Angeles, CA) is involved with creating innovative solutions using deep learning tailored to the needs of the product lines (Thorax/Retina/Cardio/Skin). We are currently hiring a full-time engineer to join our model 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 1+ years of relevant experience in building deep learning solutions for computer vision problems 1+ years of relevant experience in building deep learning solutions for NLP 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+ years of relevant experience in building deep learning solutions for computer vision problems 2+ years of relevant experience in building deep learning solutions for NLP problems Hands-on experience with Transformers, Bert, and other advanced NLP models Hands-on experience with state-of-the-art object detection, semantic segmentation, and image classification models Track record of publications in CV and NLP is a plus Hands-on experience with model optimization (e.g., network quantization and half-precision training) is a plus Prior experience with medial images is a plus Prior experience with medial report mining is a BIG plus ​​​​

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