Kognic is taking on one of the most challenging areas in AI product development—aligning humans and machines into building trusted and high-performing applications. Our platform enables businesses to get to market faster with less risk by using our toolset to define and refine datasets. We help machines reliably make sense of a messy, chaotic, and unstructured world.
Our leading market is mobility, but our future goes far beyond making automated and autonomous driving a reality. We are expanding into robotics, industrial manufacturing, and other markets to help AI product teams better understand their data.
We know we can not solve it overnight or on our own. We have to make extraordinary technological leaps, but that excites us. And we wouldn’t have it any other way!We are looking for
We are on a mission to be the driver of data conclusions across departments and time at Kognic. We see a need for a centralized ownership of production data insights, both in definitions to allow us know we are talking about the same things, but also the insights themselves, allowing us to have a shared picture of the current state.
We’re looking for an experienced data engineer who can be a strong addition to our team. As a part of the team you will provide concrete and comprehensible insights, allowing Kognicians to continuously align and adapt to reach their missions. In addition to driving insights and conclusions ourselves, we strive to enable Kognicians to self-serve data from reliable sources in our data platform. Join us to make an impact on how Kognic makes data-driven decisions!We expect you
To take an active role in the direction and execution of our mission, from the discovery phase to the development and the running of solutions.
An important part of your job will be to find out where we can make the biggest impact and how to best leverage our limited time and energy. As such it is important that you take an active role in all parts of the development process. We expect you to have a big interest in data and how to enable a data driven organization.You will
Our current tech stack
- Be part of a small autonomous and agile team
- Continue to develop our data platform
- Develop datasets for consolidating production data
- Collaborate with other teams and departments to address organization problems
- Design data visualizations to provide actionable insights
- Communicate with internal stakeholders to support their needs
Consists of Google Cloud Platform (BigQuery, Cloud Storage, PubSub, Looker Studio, Google Kubernetes Engine), Docker, Python, PostgreSQL, dbt and Airflow. Knowledge in these technologies are counted as a bonus, but not a requirement.
What’s in it for you?
At Kognic, we offer more than just a job. We provide an environment where you can work alongside talented, ambitious and collaborative colleagues in a creative and enjoyable workspace. Here's what you can expect:
- Strong values and a purpose-driven company
- Workplace flexibility with an emphasis on work-life balance
- Exciting career opportunities in a dynamic and fast-scaling startup
- Competitive work conditions and benefits; Parental pay, salary exchange, great health benefits, order your own workstation, place your own pension - to name a few.
We recommend that you submit your application as soon as possible since we will be reviewing the applications regularly & reaching out to you. We would like you to send in your resume and provide basic contact information, a cover letter is voluntary.
Kognic was conceived in the curious and bold minds of two engineering physicists who dared to dream big and bet on finding a software solution which didn’t exist.
By 2018, Daniel Langkilde and Oscar Petersson had already worked for a number of years in the field of Deep Learning when they decided to find the answer to their aspirations, and frustrations, in the entrepreneurial life to launch Kognic.
We help machines reliably make sense of a messy, chaotic, and unstructured world. The Alignment Platform™ is how we get this done. It's a pioneering toolset to help shape your data and accelerate the development of high-performing, trusted AI products.