Data and ML engineer at Norbert Health (allows remote)

About Norbert

In the future, our health will be monitored continuously by ambient sensors that will detect nearly invisible trends or changes in our habits and vital signs, and detect health problems such as infections, or deterioration in chronic conditions, before the first symptom actually occurs.

Norbert Health is building an essential device for this future: the first medical grade, contact-less vital signs scanner and health monitoring solution for the masses. It is a sleek, plug-and-play, consumer grade device that measures temperature, cardiac activity, breathing rate, and blood pressure without contact or any effort from the patient.

Our founders are uniquely positioned to deliver. Patrick Collins, CPO, built Arlo from scratch within Netgear, ran supply chain, manufacturing, distribution, and sold more than 10m cameras in four years. Alex Winter is a pioneer and repeat entrepreneur in computer vision and machine learning, started, grew and exited to venture backed startups in the field.

We are venture backed by top tier VCs, raised $9m so far, are headquartered in Brooklyn and in Paris, France. Come join us to build the future of ambient, predictive health, saving lives and making people live longer and happier, at home.

The position

We are looking for an experienced machine learning and data engineer for our AI and algorithm team, to design, develop our automated training, testing and validation infrastructure, as well as manage the massive data sets we are collecting from the field. This data includes radar images, videos, infrared videos and sound. We use the data to train our algorithms to detect, recognize and scan people’s vital signs.

Working closely with our Lead AI engineer and our CTO, you will have a unique opportunity to shape our technical architecture and be instrumental in building a revolutionary set of contactless automated health checking products.

What you will do

  • Build deep & machine learning methods on complex high dimensional data
  • Design, develop, deploy and maintain data pipelines and infrastructure to train, test and validate all our algorithms in a CI environment
  • Manage the outsourced generation of annotated data to train and test all our algorithms
  • Be the face of “algorithm accuracy and training” inside the company - provide regular reports and analysis of our performance
  • Design and implement smart ways of collecting data or derived data to test and train more algorithms
  • Design and build validation data sets and protocols to optimize and validate our predictive abilities
  • Stay on top of academic research to identify methods we should integrate
  • Be a strong contributor to the code base
  • Contribute to building a strong tech culture

What we look for

  • Expertise in data management pipelines, continuous learning systems
  • Strong coding skills in at least one language: Python, C++, Go
  • Experience in CI platforms such as gitlab, jenkins, circle-ci or others
  • Experience with Tensorflow/Keras, or other deep learning frameworks
  • Problem solving mindset
  • Genuine team spirit
  • Constant need to learn and break the barriers of technology

What we offer

  • Strong independence and decision making
  • Cutting edge, unique technology
  • A constant yearning to do better, and keep improving our technology advance
  • A talented, excellent, diverse and international team
  • A very ambitious and mission-driven vision
  • Friendly, fun, transparent culture
  • Strong incentive in the company’s future
  • A constant desire for excellence, driven by humility and drive

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