Machine Learning Engineer – Medical Imaging
This Jobot Job is hosted by: Andrew Nguyen
Are you a fit? Easy Apply now by clicking the “Apply on company site” button and sending us your resume.
Salary: $170,000 per year
A bit about us:
Based in Westwood, Los Angeles we are a fast-growing startup that offers automated medical image analysis algorithms and end-to-end solutions to help doctors make clinical decisions in a more accurate, accessible, and efficient way.
If you are an Machine Learning Engineer with prior professional experience in Python, and medical imaging, then please read on….
Why join us?
- Up to 170k Base Salary!
- Extremely Competitive Equity Package!
- Flexible Work Schedules!
- Accelerated Career Growth!
Job Details
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).
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
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, Medical Image Analysis, 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 medical images is a plus
- Prior experience with medical report mining is a plus
Interested in hearing more? Easy Apply now by clicking the “Apply on company site” button.