Machine Learning Engineer

Intelliswift$120K — $150K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • MS or PhD in a quantitative field (Computer Science, Computational Biology, etc.) with a focus on computer vision-related thesis.
  • Industrial experience in deep learning specific to image processing/computer vision or healthcare.
  • Proficient in Python with a focus on analyzing image-like data.
  • Strong foundation in supervised and semi-supervised machine learning.
  • Exceptional communication and collaboration abilities.

Responsibilities

  • Collaborate with AI and imaging scientists on machine learning projects like semantic segmentation and object detection.
  • Engage with clients and data engineers on developing end-to-end machine learning and data pipelines.

Benefits

  • Remote work flexibility.
Full Job Description
Responsibilities
- Work closely with AI and imaging scientists in machine learning work streams including but not limited to semantic segmentation, object detection and classification.
- Work closely with Client and data engineers in end-to-end machine learning and data pipelines.

Qualifications:
- MS or PhD in a quantitative field (e.g. Computer Science, Computational Biology, Machine Learning, Statistics, Mathematics, Physics), preferably with a thesis on a computer vision-related topic.
- Previous industrial experience of deep learning in image processing/computer vision or previous deep learning experience in healthcare industry or research institute.
- Demonstrated experience with Python and analysis of image-like data.
- Strong knowledge in supervised machine learning and semi-supervised machine learning.
- Excellent communication and collaboration skills.

Optional but preferred qualifications:
- Strong knowledge of classical image processing or computer vision.
- Good knowledge of Generative Adversarial Networks.
- Previous experience in medical image processing.
- Familiar with Pytorch lightning.
- Familiar with development tools for experiment tracking, dataset versioning, and model management in machine learning.

* This position is remote

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