In Continental ADAS Budapest Machine Learning Competence Center, we are creating the next generation of machine learning algorithms that power safety-critical systems and enable autonomous driving features in new cars around the globe. We are working towards Vision Zero, a goal to eliminate thousands of fatal accidents happening every day on the world’s roads. We are a diverse, dynamic and mission-oriented team of highly talented experts looking for candidates to further expand our impact.
Responsibilities:
- Create, apply and evaluate novel deep learning methods to yield a comprehensive environmental model using data from cameras, laser and radar sensors, and their combination
- Develop, analyze and improve deep learning algorithms for complex scene understanding, computer vision (2-D and 3-D object detection, semantic segmentation, human pose estimation), point cloud analysis, sensor fusion, model fusion, and more
- Access and use vast amounts of compute power and petabytes of internal and external data to train models
- Enable, perform and document evaluation and comparison of different machine learning approaches
- Work as part of an international team alongside renowned internal and external experts in the field. Benefit from university collaborations. Depending on interest, participate in real- world fields tests
Required qualifications:
- MSc or PhD from a quantitative field (e.g., computer science, electrical engineering, mathematics, physics, data science)
- Solid background and self-driven interest in machine learning, deep learning, familiarity with recent advances of state-of-the-art
- Good knowledge of computer science and general software engineering principles.
- Excellent command of English, spoken and written
- Programming experience in any of Python, C++, Matlab or excellent skills in other languages
- Collaborative, open-minded attitude, ability to work in a respectful professional team
Preferred qualifications:
- At least 2 years of relevant work experience
- Demonstrated experience in applying machine learning methods for real-world value creation
- Expertise in optimizing and fine-tuning deep neural networks
- Familiarity with GPU-accelerated libraries such as TensorFlow, PyTorch, Torch, Caffe, Theano or CNTK
- Familiarity with large-scale data processing infrastructures and technologies
- Experience in the automotive industry
What we offer:
- Participation in exciting, highly innovative projects with a leading automotive supplier
- Personal career development and challenging role in the field of deep learning
- A friendly, respectful and collaborative work environment that rewards high performance
- Competitive compensation and benefits
- Attractive working conditions including flex time and home office
- Access to cutting edge infrastructure and technologies
More information:
Szabolcs Tomko
Szabolcs.Tomko@continental-corporation.com