Internship - Machine Learning

Are you interested in Machine learning? Learn about how to use your skills to directly and ethically impact the experience of thousands of patients every day and around the world! We are looking for a student or a new gradudate with interest in artificial intelligence and visual analysis.

What You'll Do:

Our internship programs are not conventional. You’ll dive right into the heart of major projects, working with our team of passionate people, helping us create the next amazing feature. You will make a real impact on our business, and the world.

You will work on a variety of innovative and meaningful projects, from developing vision machine learning algorithms for applications such as patient monitoring, to building a training infrastructure for the core machine learning platform. Your solutions will make a significant impact in patients' healing experience and how the caretakers monitor patient well-being.

Who You Are:

You’re creative. You’re organized. You want to do this and you absolutely want to do it for us. We’re not looking for a superhero who thinks sheer hours = good work. Excess doesn’t impress us – creativity and efficiency do. You’ll have 8 hours a day to work, and, we hope, at least 8 hours a night to sleep.

Then, you are student with interest in building machine learning pipelines for activity recognition. You care deeply about bringing your unique engineering mind into creating a considerate and sustainable healthcare technology firm. You are autonomous. You’ll take full ownership of your work, and you assume the responsibility for every detail, every step of the way.

Qualifications:

Minimum Qualifications:
  • You are a student or a new graduate of Associates, Bachelor's, Master's & PhD degree or have bootcamp certification.
  • Some experience with developing Machine Learning pipelines,
  • Experience with one or more general purpose programming languages including but not limited to: C/C++ or Python.
  • Some understanding of visual recognition, classification, insight generation and similar.
  • Exposure to deep learning frameworks including Keras, Tensorflow, Caffe, Torch.
Preferred Qualifications:
  • GPU programming experience.

Benefits

We work remotely and asynchronously, and that is why we are looking for a manager of one. But you will need to overlap for a few hours with San Francisco time in your normal work-day routine - this may mean a few hours of meetings in the evening depending on your time zone - we do our best to keep them short. We can provide you with space outside of your home to work if you need to (e.g. co-working offices), or help get your home to be more accommodating to work.

We do not trap people in front of their screens or lock them in overtime. Just the opposite. We’re all about reasonable working hours and ample vacation time. See our employee handbook here.

How To Apply

We want to get a sense of how you think and work. To that end, please be prepared to share with us your take on the following:

  • Tell us what you know about machine learning. How would you begin to approach figuring out where we stand with our technology, and where we should be standing?
  • Chart us an example of a machine learning pipeline that can support the needs of modern applications (related to detecting a person's activity)
  • What technologies inspired you recently? What machine learning technologies are you the most excited about?

We strongly encourage candidates of all different backgrounds and identities to apply. Each new hire is an opportunity for us to bring in a different perspective, and we are always eager to further diversify our company. Ouva is committed to building an inclusive, supportive place for you to do the best and most rewarding work of your career.

We value great writers, so take your time with the application and put thought into your cover letter if you are writing one, but keep it fewer than 1500 words. Tell us why you want this job, not just any job.

We can’t wait to hear from you!


To apply for this position, please send your resume, supplemental materials and letter to hello@ouva.co