Senior Deep Learning Engineer

Job title:

Senior Deep Learning Engineer

Company

Continental

Job description

Company DescriptionContinental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent and affordable solutions for vehicles, machines, traffic and transportation. In 2024, Continental generated preliminary sales of €39.7 billion and currently employs around 190,000 people in 55 countries and markets.Job DescriptionIn the Budapest Artificial Intelligence Development Centre of Continental, we create next generation automotive software solutions which make automated driving safe and affordable. We work towards Vision Zero, a goal to eliminate fatal accidents happening every day on the world’s roads. In the Business Area of Autonomous Mobility, we are looking for creative minds who are passionate to shape the future of automated driving by delivering world-class perception and fusion systems.
Our teams develop software solutions for Driver Assistance (DA) and Automated Driving (AD) Systems, processing various automotive sensor data and providing a robust, scalable output to driving function modules.Your TaskAs a Deep Learning Engineer You will:

• 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 computing 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 field tests.

Qualifications

• MSc or PhD from a quantitative field (e.g., computer science, electrical engineering, mathematics, physics, data science).
• At least 3 years of relevant work experience.
• Solid background and self-driven interest in machine learning, deep learning, familiarity with recent advances of state-of-the-art.
• Expertise in optimizing and fine-tuning deep neural networks.
• Programming experience in any of Python, C++, Matlab or excellent skills in other languages.
• Demonstrated experience in applying machine learning methods for real-world value creation.
• Familiarity with GPU-accelerated libraries (e.g., PyTorch, TensorFlow)
• Good knowledge of computer science and general software engineering principles.
• Excellent command of English, spoken and written.
• Collaborative, open-minded attitude, ability to work in a respectful professional team.

Nice to have

• Familiarity with large-scale data processing infrastructures and technologies.
• Experience in 3D Computer Vision and Multimodal models
• Experience in the automotive industry.

Additional InformationWhat We Offer

• Participation in exciting, highly innovative projects.
• Personal career development and a challenging role with end-to-end responsibility.
• Ability to directly deliver software into real products.
• Opportunity to see your ideas turn into reality with our test vehicle.
• Continous development with access to numerous trainings, including technical skills, soft skills and language skills.
• A friendly, respectful and collaborative work environment that encourages creativity and innovation.
• Competitive compensation and a wide range of benefits, including:

• Private health insurance
• Bonus system
• Employee discounts
• Sport pass support
• Easily accessible office location.

Ready to drive with Continental? Take the first step and fill in the online application.

Expected salary

Location

Budapest

Job date

Wed, 12 Mar 2025 01:15:36 GMT

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