Machine Learning Engineer for Autonomous Driving - ADAS (TM)
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Employer: | Continental |
Domain: |
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Job type: | full-time |
Job level: | 0 - 1 years of experience |
Location: |
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Updated at: | 06.04.2022 |
Remote work: | On-site |
As part of AE - Advanced Engineering team you will be able to contribute to developing concepts for Autonomous Driving Systems, based on state of the art technologies and beyond. Main focus is on applied research in machine learning, aimed at solving problems and tackling real-world challenges, with emphasis on innovation.
The Machine Learning Engineer will have the following responsibilities:
* Understand, implement and analyze the state-of-the-art;
* Propose and develop new concepts;
* Design machine learning systems;
* Research and implement appropriate ML algorithms and tools;
* Develop machine learning applications according to requirements;
* Select appropriate datasets and data representation methods;
* Run machine learning tests and experiments;
* Perform statistical analysis and fine-tuning using test results;
* Train and retrain systems when necessary;
* Extend existing ML libraries and frameworks.
Job Requirements:
* Experience as a Machine Learning Engineer or similar role;
* Understanding of data structures, data modeling, and software architecture;
* Deep knowledge of math, probability, statistics, and algorithms;
* Ability to write robust code in Python;
* Familiarity with machine learning frameworks (like Keras, TensorFlow, PyTorch).
What we offer:
Pay for Performance:
* Achievement Bonuses and Rewards;
* Relocation Bonus for non-Timisoara Residents;
* Recommendation Bonuses for new team members;
* Flexibility Program including flexible hours, mobile work and sabbaticals.
Wellbeing:
* Health & Wellness (Private Health Insurance, Life Insurance, Sport activities etc.);
* Different discounts (glasses, tires, medical, shopping);
* In-house restaurant & coffee corners.
Life-Long Learning:
* Technical, Soft Skills & Leadership trainings;
* Dedicated Programs and Conferences;
* Free Language Courses (English, German, French etc);
* Access to e-learning platforms;
* Career development opportunities (local and international);
* Internal development communities (Experts, Agile Community of Practice, Artificial Intelligence etc).
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