You are viewing a preview of this job. Log in or register to view more details about this job.

Machine Learning Engineering Intern For a Stealth AI Startup

Are you experienced with deep learning/computer and looking to make a big impact in healthcare?

The last 12 months has seen a dramatic shift toward digital health, driven by the COVID-19 pandemic. However, it is difficult to provide a similar level of care on a video call as during an in-person visit. While the physician can use visual observation and self-reported symptoms to diagnose a patient, they cannot objectively assess the patient’s physiological state. This means that physicians have to make decisions without important data.

Our Stealth AI Healthcare Startup is focused on making a suite of tools to measure patient health in the home. Our technology is based on cutting-edge research from some of the top AI for Health research labs in the world.

We are seeking an amazing ML engineering intern to help build Computer Vision (CV) deep learning algorithms for our suite of healthcare products. In this role, you will work alongside world leaders in AI for healthcare to develop, train, and evaluate new ML models to measure important health metrics. Our four-person founding team is comprised of experts from the AI, healthcare, software engineering, and clinical fields.

We invite you to join us in making quality healthcare more accessible to patients across the globe.

To be successful in this role, it would help if you have:
  • Passion for building tools that can meaningfully impact the healthcare industry
  • Fascination with the latest research in deep learning
  • Collaborative spirit and willingness to work closely with colleagues toward a shared goal
  • Growth mindset and desire to continually improve your technical skills

Qualifications:
  • Background in designing and developing Computer Vision algorithms
  • Experience in Python and ML frameworks such as: Tensorflow, Keras, Pytorch, Caffee, etc
  • Proficiency in deep learning model architectures such as convolutional, residual, attentional, and recurrent neural networks
  • Ability to understand recent deep learning research papers and adapt those models to solve real world problems
  • Ability to effectively multi-task and adapt within a fast-paced environment
  • Excellent communication and organizational skills