Machine Learning Engineer - Computer Vision & NLP

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 engineerto 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 ​​​​

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.