Machine Learning Engineer

About the job

Machine Learning Engineer – Medical Imaging

This Jobot Job is hosted by Andrew Nguyen

Are you a fit? Easy Apply now by clicking the “Apply” 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” button.

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