Machine Learning Engineer

You will be part of one of Smart Eyes algorithm development teams responsible for development in key areas such as head- and eye-tracking attentiveness and drowsiness face identification and interior sensing for our Automotive Cabin and Driving Monitoring product. We work in an international environment with colleagues in Gothenburg (SE) and Boston (US).

We are building safety features in novel technology that will significantly improve road safety and will transform our transportation experiences. Safety features such as determining peoples seating locations in a vehicle if they are wearing seat belts and detection of left-behind children as well as features that enhance comfort wellness and entertainment by detecting occupants emotions and gestures.

Development activities range from early-stage prototyping to porting and deployment to a wide set of automotive embedded platforms. And you will be responsible for the complete chain of development activities including protocols for data collection network architecture training of networks exploratory data analysis and visualization but also integration into and validation of the model in the production software.

We solve these challenging problems by utilizing state-of-the-art algorithms in the fields of image processing the latest machine learning techniques mathematics and accelerated computing.

You will have an active impact on the processes and projects and will work in close cooperation with other talented team members. Your contribution to how we can meet our customers needs with tomorrows technology will be of crucial importance.

Who are you

We welcome all types of personalities and believe in a true mix of people to create a dynamic work environment.

Youre able to work independently in an environment that changes rapidly.

Exhibit a positive enthusiastic open entrepreneurial attitude and a willingness to work closely with customers or other teams within Smart Eye.

Possess strong analytical creative skills with a strong interest in new technologies.

Must-have-skills:

Degree in Electrical Engineering Computer Sciences or Mathematics with specialization in computer vision or machine learning.

Experience using end-to-end development of machine learning based systems (design planning evaluation deployment).

3 years of software development experience.

3 years of work experience in C and Python development.

Strong communication and team collaboration skills.

Good-to-have-skills:

Experience in optimizing Deep Learning model architectures and inference runtimes (ex. Tensorflow Tensorflow Lite PyTorch).

Experience in one or more fields of image processing or graphics programming.

Experience with CI/CD (Continuous Integration and Deployment).

Experience in developing software for the Automotive industry.

Familiar with Agile methodologies (has worked with Git Jira and alike).

Smart Eye is the leading provider of Human Insight AI technology that understands supports and predicts human behavior in complex environments. The company is on a mission to bridge the gap between humans and machines for a safe and sustainable future. Supported by Affectiva and iMotions companies it acquired in 2021 Smart Eyes multimodal software and hardware solutions provide unparalleled insight into human behavior.

In automotive Smart Eyes driver monitoring systems and interior sensing solutions improve road safety and the mobility experience. The companys eye tracking technology and iMotions biosensor software platform are also used in behavioral research to enable advanced research in academic and commercial media analytics Affectivas Emotion AI provides the worlds largest brands and market researchers with a deeper understanding of how consumers engage with content products and services.

Founded in 1999 Smart Eye is a global company headquartered in Sweden with customers including NASA Nissan Boeing Honeywell Volvo GM BMW Polestar Geely Harvard University 26 percent of the Fortune Global 500 companies and over 1300 research organizations around the world.

Visit for more information.