Deep Learning Engineer

Cloudinary is the leading provider of media management solutions, powering the trusted, award-winning visual experiences for many of your favorite brands. Cloudinary is the de facto media platform standard for developers and brand managers looking to upload, store, transform, manage, and deliver images and videos online. With more than 40 billion assets under our management and 7,000 customers worldwide, we’re always looking for exceptional people to help us reach for the cloud.
Cloudinary is at an exciting stage, rapidly expanding its product offering, entering new market segments, and extending the customer base. We offer a fun, supportive environment in which you will constantly learn and evolve; a place where your ideas will be embraced and pursued. We are proud of our collaborative, and growth-minded work culture, being included in Forbes Cloud top 100 three times in a row and being a multi-time winner of the “best place to work” award as evident by our Glassdoor score.
We are looking for a team member who's passionate about new technologies and loves challenging engineering technical problems. Using existing tools and solutions or writing from scratch. As a member of the Platform team, you will help enhance, design, own, and maintain Cloudinary’s Machine Learning infrastructure


  • Solutioning, Developing, and maintaining Machine Learning infrastructure
  • Fast integration and updates of algorithms into Cloudinary's backend infrastructure
  • Improve our own AI training platform
  • Technical optimizations of Deep Learning networks
  • Build our own inference engines
  • Leading an end to end engineering solutions, taking research work all the way to production
  • Experiment with new tools, Cloud solutions, 3rd party libraries, and frameworks


  • 5+ years of experience in application design and development
  • Experience in working with large scale, distributed cloud-based architectures
  • Strong understanding of web technologies and architecture


  • Experience with Python
  • Experience with AI development frameworks such as Pytorch, Tensorflow
  • Familiar with MLOps tools like MLFlow, Tensorboard, SageMaker, Trainz or the like

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