Job
In this role, you will configure and integrate embedded software for driver assistance systems and develop deep learning models based on vehicle sensor data to optimize ADAS functionalities.
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Job technologies
Your role in the team
- Configuration and integration of embedded software for driver assistance systems.
- Development and customization of, for example, deep learning models for ADAS functions based on vehicle sensor data.
- Selecting suitable network architectures such as CNN, RNN, Transformer, GAN, or BEV.
- Training and optimizing models on a GPU cluster as well as in the Azure Cloud.
- Conducting performance analyses, hyperparameter tuning, and quality assessments.
- Optimizing networks for deployment on vehicle control units in terms of runtime, memory, and robustness.
- Close coordination with functional developers, software architects, and cloud teams along the entire ADAS data chain.
- Sharing AI expertise with colleagues through coaching, reviews, and internal training.
Our expectations of you
Education
- Completed engineering degree in Technical Informatics/Electrical Engineering/Embedded Systems or a comparable field.
Qualifications
- Excellent knowledge of Python.
- Proficient in Keras, TensorFlow, PyTorch, and JAX.
- In-depth understanding of training and optimization methods, particularly SGD variants and adaptive optimizers.
- Experience in using Azure for training, data management, and experiment administration.
- Confident handling of Git, code reviews, testing, and clean software engineering.
- Ability to clearly communicate AI expertise and provide professional support to colleagues.
- Structured working method.
- Good German and English language skills, both written and spoken.
- Knowledge of relevant standards such as ISO 26262, SOTIF, or Automotive SPICE.
Experience
- Extensive experience with modern network architectures such as CNN, RNN, Transformer, GAN, and BEV.
- Experience in training deep learning models on GPU systems as well as in multi-GPU environments.
- Experience in optimizing models for embedded platforms and control units, including quantization and model compression.
- Experience in the automotive or ADAS environment.
- Experience with MLOps concepts such as reproducible training pipelines or model versioning.
- Practical experience with Docker or GPU cluster scheduling, experience in data engineering topics such as data quality or building data pipelines.
What we offer
- Competent and personalized onboarding.
- Interesting and challenging activities in an innovative environment.
- Very good prospects and attractive conditions.
- Flat hierarchies and active participation in shaping.
- Very pleasant working environment.
- Flexible working hours.
Benefits
Work-Life-Integration
Topics you will work on
Job locations
About your employer
Venteq GmbH, based in Chemnitz, develops specialized software solutions for the automotive industry, including software components and complex algorithms for driver assistance systems, object recognition, navigation, and autonomous driving. Since November 2022, the company has been part of CARIAD SE and thus belongs to the Volkswagen Group.
- Established Company
- Onsite
- Vehicle Manufacturing, Supplier
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