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Machine Learning Engineer - Autonomy with dual-use application

Einride AB

Sammanfattning

Einride is seeking a Perception Engineer to advance multi-modal perception and localization systems for autonomous platforms. The role involves researching and developing perception algorithms, optimizing machine learning solutions, and collaborating with various teams to ensure the deployment of effective perception systems. This full-time position is based in Gothenburg and is ideal for candidates with a strong technical background in robotics or AI and experience in perception-related fields.
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Arbetstid

heltid


Göteborg

Ansök senast: Öppet tillsvidare
Publicerad: 2026-09-08

Beskrivning

Want to be part of transforming road freight? Einride is showing the world a new way to move, based on the latest digital, autonomous and electric technologies. We build the technology that hauls freight efficiently, and we put it to work for the world's leading manufacturers, retailers, logistics providers and defense organizations, all working toward a future where moving goods cost less for our customers, and less for the planet.

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 U.S. public road. In June 2026, Einride became a publicly listed company on Nasdaq, a milestone that reflects a decade of turning what once looked like science fiction into everyday reality. Today, our technology moves freight across North America, Europe, and the Middle East for some of the world's biggest shippers.

We are looking for an Machine Learning Engineer with a strong interest for multi-modal perception systems for autonomous platforms. The ideal candidate has software engineering and machine learning skills, preferably with experience designing, developing, and transitioning R&D solutions into fielded, mission-ready systems.

You will:
  • Design, train, and optimize ML/DL solutions for sensor fusion, 3D object detection and classification, scene understanding, segmentation, tracking, behavior modeling
  • Build and maintain data and training pipelines (curation, labeling, augmentation, evaluation), including for limited or sensitive data, and drive continuous performance improvements
  • Keep sensors accurately calibrated and aligned across the sensor suite, and correct drift caused by varying field conditions
  • Integrate, validate, and deploy production-ready solutions, including optimizing models for real-time inference on embedded, SWaP-constrained, and ruggedized hardware.
  • Collaborate closely with System Engineering, Planning, and other teams to build a safe, resilient, and deployable perception stack

We expect you to have:
  • Preferably 3-5+ years of work experience with strong technical background in Robotics, , Machine Learning, Computer Science, Artificial Intelligence or Mathematics.
  • Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and end-to-end model development
  • Strong foundation in linear algebra, probability/estimation theory, data structures, algorithm design, and complexity analysis
  • Experience with C/C++ and Python, and strong problem-solving skills
  • Ability to obtain and maintain a security clearance
  • A problem solving mindset and self-starting attitude that can be demonstrated through hobby programming or own robotics projects

This is a full-time position based in Gothenburg. We recommend that you submit your application as soon as possible since selection and interviews are held continually.

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.

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Machine Learning Engineer - Autonomy with dual-use application

Denna arbetsplats har annonserats på Compilation Source (Sweden)-tjänsten den 2026-09-08 och publicerades av Compilation Source (Sweden).
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Einride AB
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