Hi there. We are dQmetrics, and we are looking for a machine learning engineer who can lead the development of our machine learning algorithm and guide our sensor selection.  

The idea is to develop a wearable smart ring, which can track the daily food calorie intake automatically. The ring will collect detailed heat data on the energy, which is used to absorb and digest food. Compared to existing smart watches, we will add several new sensors, including a heat flux sensor and an infra-red temperature sensor. We want to use the combined sensor data to predict the calorie intake via a machine learning algorithm. In the coming month, we expect to run the initial feasibility study, where we use our prototype to collect the first live testdata from a testperson. You will start working on this data and begin designing the ML algorithm.

You will be working closely together with our hardware developer regarding the data structure and the sensor selection. The framework and language for the machine learning algorithm has not been chosen yet. Currently, we got a crude prototype, where the first batch of sensors is integrated and set up on a printed circuit board (pcb).

What’s in it for you?

• Become co-founder in a deep tech startup with the potential to help millions of people lose weight

• You get to build an innovative product, that’s never been done before

• Become part of the vibrant and fast paced hardware incubator, Futurebox (which is located in DTU Science Park)

• You get to work with ambitious and experienced entrepreneurs

• Lots of fun, friday bars and social events    

About dQmetrics:

We’re an early-stage deep tech startup and we are passionate about developing the next generation of wearables. We believe, the wearables industry is just getting started, and that there is a huge market opportunity in expanding the range of available sensors to unlock the secrets of the human body. Currently, we are two co-founders. We got the business background and the hardware developer covered. Besides you, we expect to onboard a co-founder with a background in physiology to account for the biological differences from person to person.

Preferred skills:

• You have coded and trained neural networks from scratch

• You have a solid understanding of the full cycle of machine learning algorithms, from design and data structure to implementation and optimizations

• You have a general knowledge of software development

Timeline:

We aim to apply for an Innofounder grant in September 2022, where we hope to include you as co-founder. If we get the grant, we will be able to offer a paid full-time position with equity on top from the first of January 2023. Until then we are quite flexible and account for your situation. The salary will be able to sustain you, but it’s small for the first year.  

Are you the co-founder we are looking for?

Then, we would love to hear from you. Applications are reviewed continuously.