Data Science Engineer Computer Vision

Found in: Talent CN S2 - 1 week ago

Suzhou, China Bosch Full time
Job Description

As a data science engineer you are responsible for the development and execution of tools that serve the machine learning development (computer vision) in the field of assisted and automated driver assistance systems (ADAS). You develop data mining algorithms and embed them into tools that can handle large amount of measurement data from vehicles; the focus is on computer vision.

Job Responsibilities

· You are responsible for the definition of a data engineering and AI-based data science strategy for the development of computer vision algorithms of the camera for ADAS within the department. For that you scout state of the art tools and methods, define the right toolchain, and adapt them to the department’s use cases and needs.

· You work closely with the development teams which train and deploy deep learning algorithms on the embedded hardware. These teams define data mining needs for deep learning model training, verification, and testing (scenarios, use cases), where the performance should be further improved. You define ways to assure the representativeness of the data.

· You design technical solutions to achieve the data mining needs in an efficient way. For that, you and the team train own data mining algorithms and use other advanced methods ( CLIP). You further strive for a high level of automation and precision with AI-based state-of-the-art (SOTA) solutions. You define the way how to achieve further advancements towards auto-labeling, auto-tagging, auto-quality-check, auto-filtering, and auto-triggering.

· You collaborate with other departments and organisations both domestically as well as globally within Bosch. You identify synergies and actively use them for the department.

Qualifications

Qualification Requirements (Skills /Experience/ Education/Behavior)

degree in computer science, automotive or electronic engineering

years working experience in data engineering, deep learning based model design and deployment; preferably in computer vision.

3.Proficient in python, experienced in data management solutions

4.Proficient in some of these tools (or related solutions): PyData stack, Pandas, tableau/PowerBI or similar, Gephy/Force Atlas 2, Voxel51, MongoDB, MySQL, QT, Kafka.

5.Proficient in Deep Learning frameworks，such as PyTorch, Tensorflow

6.Proficient in popular DL task model, such as semantic segmentation model, image classification model, object detection model and image generation model.

7.Experienced in machine learning algorithms, especially in state-of-the-art deep learning algorithms

8.Experienced in AI-model deployment and compression techniques.

9.Experienced in using cloud computing solutions, know-how in edge-cloud deployment.

10.Experience in international team communication

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