ML-engineer co-founder to Wearable Startup

1 week ago

København, Denmark The HubDanske Bank Full time

Hi there. We are dQmetrics, and we are looking for a Machine Learning engineer who can lead our algorithm development.

We are developing a wearable wristband that can auto-track the calories consumed - without manual meal registration. The goal is to make lasting weight change possible for slightly obese individuals. We have working prototypes and have just finished our proof of technology, demonstrating that the concept works in laboratory settings. Now we are preparing for closed customer testing, where test persons will wear our prototype as a normal smartwatch in real-world settings. As a result of this testing, we expect to scale our data collection significantly, allowing us to develop and train more advanced algorithms. We need your help to take our algorithms to the next level, so our test users can get accurate calorie predictions continuously.

We are looking to raise our first investment round in the coming 3-6 months. When we raise our first round, we can offer equity and a salary that will sustain you. In the meantime, we expect the position to be part-time with around 5 to 20 hours per week. During this period, you will start earning vested equity, but the position will be unpaid. We are quite flexible around the part-time period and take your situation into account.

What’s in it for you?

  • Impactful Work: We are pushing the technology frontier with a new product that can make a real difference for people living with obesity.

  • Critical Role: Your algorithms will be an essential part of our product and company.

  • Continuous Growth: You get ownership and influence over the design, development, and operations of our algorithms.

  • Collaborative Culture: Thrive in a team that cares. Our environment is built on collaboration, mutual respect, and a shared passion for innovation.

  • Multidisciplinary Team: Being in the wearable space, you get to work at the intersection between Hardware, Software, Machine Learning, and Health Sciences.

About the role:

Our primary algorithm uses sensor-based time-series data. Currently, we have a working operational pipeline, with data pre-processing, feature engineering, training, and deployment of our algorithm. In the beginning, the primary focus will be on developing and training a new neural net model for our calorie-prediction algorithm. Over time, we need additional algorithms to support new features and insights for the users.

In the short term, we are looking for someone who can make things work fast and iterate to improve our algorithms. As our company grows, you’ll have the opportunity to shape your future role based on your interests—whether that means leading our data science efforts, focusing on building new algorithms, or improving operations.

About dQmetrics:

We’re an early-stage deep tech startup passionate about developing the next generation of wearables. We believe the wearables industry is just getting started, and there is a huge market opportunity in moving away from traditional vital sign sensors and expanding the range of sensors to unlock the secrets of the human body. Currently, we are a team of two, covering business and hardware development. Besides you, we are looking to onboard a Software engineer.

Preferred skills:

  • Experience with rapid prototyping and iterative development.

  • Experience with developing algorithms from scratch and seeing the process through to production and continuous improvement.

  • Experience with Python.

  • Strong problem-solving skills and an analytical mindset.

  • Eagerness to learn and a proactive attitude.

  • Works well in a team.

Nice to have:

  • A great understanding of math/statistics.

  • A basic understanding of time-series data.

  • General knowledge about GitLab is a plus.

Are you the co-founder we are looking for?

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

#J-18808-Ljbffr

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    1 week ago

    København, Denmark The HubDanske Bank Full time

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