Internship Deep Learning Labeling for ADAS (TM)

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Employer: Continental
Domain:
  • Engineering
  • Job type: part-time
    Job level: 0 - 1 years of experience
    Location:
  • Timisoara
  • Updated at: 06.04.2022
    Remote work: On-site

    Each one of us can contribute to a better future. You can do this on a daily basis on a labeling role.

    ADAS (Advanced Driver Assistance Systems) department develops products and systems based on intelligent Camera, Radar & Lidar sensors that are able to "see" and collect details from traffic in the surrounding area of the vehicles.

    By joining our team, you will be part of the Labeling group for Deep Learning activities. Focus area covers Camera, Lidar and Radar technologies.



    * You will be labeling the data that comes from the different sensors based on the requirements agreed with the development.
    * You will provide essential data to algorithms implemented using Deep Neural Network, and covering Object Detection, Lane detection, Semantic Segmentation, etc.
    * You will be working together with the algorithm development team to find the best possible solution for data annotation.
    * Highly flexible work.
    * Technical university/technical knowledge not needed.

    A mentor will support you to stepwise take over own responsibility after an initial training phase which will familiarize you with our products, tools, processes and organization.

    Job Requirements:



    * Currently studying at University;
    * Quality oriented, responsible, determined;
    * English language;
    * Highly motivated and willing to get involved in technical projects;
    * Detail oriented mind;
    * 8 hour availability Would be a plus:
    * Hungarian language,
    * German language,
    * Automotive knowledge,
    * Experience in activities related to data labeling, data marking, data annotation, test and validation.

    What we offer:



    * Integration Program in a professional, young & dynamic team;
    * A mentor for your learning period;
    * Competitive Salaries & Benefits;
    * Recommendation Bonuses for new team members;
    * Flexible working hours for your studies.

    Wellbeing:



    * Health & Wellness (Private Health Insurance, Life Insurance, Sport activities etc.);
    * Different discounts (glasses, tires, medical, shopping);
    * In-house restaurant & coffee corners

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