AI Data Engineer
AI Data Engineer
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Job Description
At Continentals Budapest Artificial Intelligence Development Centre within the Autonomous Mobility business area we develop nextgeneration automotive software to make automated driving safe scalable and costeffective. We are seeking passionate and innovative professionals to shape the future of autonomous mobility.
Join one of our Data engineering team where we focus on building and maintaining highperformance data infrastructure to support the development of automated driving functions. We process data from multiple sensor modalitiesincluding LiDARs radars and camerasand ensure its quality consistency and usability across various downstream teams. This includes enabling largescale automotive data labeling workflows such as lane and object annotation and supporting sensor calibration processes to ensure synchronized and accurate inputs. We develop scalable data pipelines that identify relevant driving scenarios and edge cases enrich raw data with metadata and ground truth information. We also tackle stateoftheart challenges by automating complex processes such as label quality validation and data selection through intelligent datadriven techniques. Our solutions are built on a cloudnative stack primarily leveraging AWS and Python to provide efficient access to structured highquality datasets for AI and perception system development.
Our work includes
- Processing and validating multimodal sensor data from LiDARs radars and cameras
- Developing automated data labeling pipelines and enrichment tools to extract edge cases
- Creating and managing searchable highquality datasets for training and validation of AI models
- Integrating all data solutions in a cloudnative stack using Python
Your Tasks
- Design develop and maintain highperformance data pipelines tailored to automotive datasets
- Collaborate closely with AI engineers perception experts and labeling teams to enable datadriven development
- Process and filter sensor data to extract meaningful scenarios and enrich datasets for model training
- Implement cloudnative solutions (AWSbased) for efficient data storage processing and access
- Apply your understanding of sensor calibration automotive labeling standards and data quality validation
- Continuously improve data workflows from ingestion to consumption by turning requirements into productionready solutions
Qualifications :
- BSc/MSc in Computer Science Electrical Engineering or a similar fieldor equivalent professional experience
- 3 years of experience in software development preferably in dataintensive environments
- Experience in automotive data labeling workflows such as lane annotation object tracking or ground truth generation
- Practical experience working with multimodal sensor data (LiDAR radar camera)
- Understanding of sensor calibration techniques and data synchronization
- Strong Python programming skills
- Good written and spoken English
- Comfortable working independently and as part of an international crossfunctional team
Nice to Have
- Experience with AWS
- Familiarity with agile software development
- Background in machine learning or AIbased perception systems
Additional Information :
What We Offer
- Participation in exciting highly innovative projects.
- Personal career development and a challenging role with endtoend 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 in downtown Budapest (near Klvin square).
Ready to drive with Continental Take the first step and fill in the online application.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
