Want to be part of transforming road freight – for good? Einride is showing the world a new way to move, based on the latest digital, electric and autonomous technologies. Through our offering – freight capacity as a service – we enable businesses around the world to accelerate towards their sustainability goals.

Founded in 2016, Einride became the first company in the world to deploy a cab-less autonomous electric vehicle on a public road (Sweden, 2019). In 2022, we were the first to successfully operate such a vehicle on a US public road. Today, we are a team of more than 500 people, and our award-winning technology is being deployed across 8 countries (and counting). Our clients include some of the world’s biggest shippers, including Fortune 500 companies.

We are looking for enthusiastic, humble and creative Machine Learning Engineers who are passionate about creating simple, beautiful and helpful solutions to empower the public and the transport business. As a Machine Learning Engineer at Einride, you will join one of our top talent teams where you will have the opportunity to innovate and drive change together with other ambitious, innovative and kind-hearted people who all challenge conventional thinking.

At Einride you will design, implement and optimize models for production systems, enabling safe and performant autonomous driving. There will also be exploration, prototyping and evaluating state of the art algorithms. You will be a part in developing core deep learning software for efficient training, testing and deployment pipelines and be considered one of the technical leaders in the field, mentoring and leading others to become productive and guiding technology decisions.

We expect you to:

• Be strong in programming skills such as; C++, Python, or similar languages
• Have in-depth understanding of common and recent Machine Learning and Deep Learning architecture(s)
• Previous experience in design, training, and analyzing deep neural network for at least one of these specific areas: 2D/3D object detection, classification, semantic/instance segmentation, activity recognition, sequence learning, multi-task learning, multi-object tracking(visual/LIDAR), sensor fusion and motion prediction
• Have experience working with LIDAR and/or camera data, large datasets, self-supervised and/or semi-supervised learning and sensor calibration
• Knowledge within deep-learning frameworks such as PyTorch (or others)
• Deep knowledge within linear algebra, probability and statistics theory

This is experience or knowledge we consider a bonus:

• PhD in machine learning, computer vision, robotics or related field
• Experience working on autonomous vehicles, or related fields
• Experience using Go
• Experience in optimization & deployment of deep learning models in real-world environments

We recommend you submit your application as soon as possible as selection and interviews are held continuously.

Please note that as part of our standard recruitment process, we conduct a background control on the final candidate for this role. This may include verification of education, employment history, any relevant professional certifications or other information that may be of our interest.

At Einride, we are innovators, building solutions the world has never seen before – but urgently needs. That’s why we take action, and it’s why we are always eager to be challenged. We know that our best innovations come from having a diverse mix of people, including those of different experiences, career paths, and walks of life. By coming together and sharing our perspectives openly – by disagreeing, discussing, and committing – we deliver greater impact.