Full Stack Engineer with Machine Learning
About the team
We are now looking for a Full Stack Engineer for one of our development teams! Founded in 2018, Kognic is the data platform accelerating machine learning for performance-critical applications. Through our proven MLOps tools, we empower automotive engineers and product teams to develop and deploy ADAS/AD systems in measurable and cost-efficient ways. We are an ambitious team building a global company together.
The Role
You will join one of the teams within one of our product areas. The team's mission is to get data and predictions into the hands of annotators, and as a developer, you will work on developing new features in our existing applications. You will be helping us to maintain public-facing APIs that work with data on the order of terabytes per month, developing and publishing client libraries for those APIs to public package repositories and improving our ML prediction tools for efficient annotation. Occasionally we also work on features that reach full stack, from UI to infrastructure, so front-end work is also possible. As part of a team, you succeed with the team. At Kognic, we empower our teams to be bold and make decisions; you are the ones closest to the information. You own your mission, and you are vital to our success. Our teams are agile, autonomous and self-improving. They discuss needs with users and clients and negotiate priorities with stakeholders. The teams are end-to-end responsible for the things they build.
Our Tech Stack
Our platform is modularly built using TypeScript and React. We develop our backend with Scala and Python and deliver the complete solution using Kubernetes on Google Cloud. We rely on ElasticSearch to enable real-time search capabilities.
Who you are
We believe you are a person with high ambitions and a passion for Software.
You have:
A higher level education, preferably within software engineering, computer science, engineering physics, engineering mathematics, or similar (can be weighed up by relevant experience)
Experience with backend development or ML/algorithms
Polyglot with at least one of Python, Scala, Java, Rust, Javascript, or Typescript
Keen on writing well-tested, maintainable code
Familiarity with a frontend framework such as React. Preferably from working on an application (vs a website)
Nice to have:
Familiarity with functional programming
Familiarity with Cloud Computing (Google Cloud, AWS, Azure)
Familiarity with containerisation, Kubernetes & similar
Experience with 3D mathematics
Experience with graphics
What is in it for you?
Other than working with our excellent team in an inspiring and collaborative environment, we also offer you this:
Strong values and purpose-driven company
Being part of defining and building the ground truth product
Workplace flexibility and work-life balance
Competitive salaries
Exciting career opportunities in a dynamic and fast-scaling startup!
Parental pay, salary exchange, maximum health benefit, order your workstation, 30 days vacation, place your pension – to name a few.
Application
We recommend you submit your application as soon as possible. We select and interview continuously. If you have any questions regarding the position, please contact our Talent Acquisition Partner: padma.subramanian@kognic.com
About Kognic
Kognic was founded in 2018 by Oscar Petersson and Daniel Langkilde, two engineering physicists working in the field of Deep Learning. Our mission is to make safe perception for autonomous mobility possible. We now support world-leading companies in Autonomous Driving, Advanced Driving Assistance Systems and Active Safety development worldwide. Our office is at Lindholmen, just by the beautiful waterfront and Lindholmen Science Park.
- Departments
- Engineering
- Locations
- Gothenburg, Sweden
- Remote status
- Hybrid Remote

Gothenburg, Sweden
About Kognic
Kognic provides the data platform accelerating machine learning for performance-critical applications.
Kognic's proven MLOps tools empower automotive engineers and product teams to develop, test and deploy ADAS/AD systems in measurable and cost-efficient ways.
the relentless pursuit of performance and trust.
Full Stack Engineer with Machine Learning
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