Join our company's REM (Road Experience Management) department – the team driving the automatic creation of High-Definition maps, a cornerstone technology behind our company's autonomous driving and advanced driver-assistance systems.
REM map creation leverages cutting-edge algorithms executed at massive scale using Big Data technologies, requiring both a deep understanding of the map creation pipeline and strong technical expertise.
You will be part of our Priority Semantics algorithmic team, focused on understanding right-of-way rules and interactions derived from traffic signs, road structures, and driving behavior.
The team uses cutting-edge technologies, including Graph Neural Networks (GNNs) and data-driven learning techniques, to model complex driving scenarios and extract meaningful insights from large-scale real-world driving data.
This role requires a deep understanding of the data itself, modeling complex semantics, and extracting insights using learning-based approaches to accurately represent real-world driving priorities.
What will your job look like?
Design, train, and evaluate cutting-edge deep learning models on REM proprietary map data
Perform high-scale, large-volume data analysis
Integrate new map-based algorithms with full ownership
Develop tools that enable fast and effective data introspection
Optimize models and results where needed.
REM map creation leverages cutting-edge algorithms executed at massive scale using Big Data technologies, requiring both a deep understanding of the map creation pipeline and strong technical expertise.
You will be part of our Priority Semantics algorithmic team, focused on understanding right-of-way rules and interactions derived from traffic signs, road structures, and driving behavior.
The team uses cutting-edge technologies, including Graph Neural Networks (GNNs) and data-driven learning techniques, to model complex driving scenarios and extract meaningful insights from large-scale real-world driving data.
This role requires a deep understanding of the data itself, modeling complex semantics, and extracting insights using learning-based approaches to accurately represent real-world driving priorities.
What will your job look like?
Design, train, and evaluate cutting-edge deep learning models on REM proprietary map data
Perform high-scale, large-volume data analysis
Integrate new map-based algorithms with full ownership
Develop tools that enable fast and effective data introspection
Optimize models and results where needed.
Requirements:
3+ years of industry experience, including at least 1 year of experience in machine learning
MSc in Computer Science, Electrical Engineering, or a related engineering field
Strong experience in Python
Familiarity with numerical and data science frameworks such as NumPy, Pandas, SciPy, PySpark, TensorFlow, and PyTorch
Linux knowledge and some familiarity with AWS
A get it done approach and a flexible mindset
Experience working with AI agents or coding assistants (e.g., Copilot) – an advantage
Familiarity with Graph Neural Networks (GNNs) – an advantage.
3+ years of industry experience, including at least 1 year of experience in machine learning
MSc in Computer Science, Electrical Engineering, or a related engineering field
Strong experience in Python
Familiarity with numerical and data science frameworks such as NumPy, Pandas, SciPy, PySpark, TensorFlow, and PyTorch
Linux knowledge and some familiarity with AWS
A get it done approach and a flexible mindset
Experience working with AI agents or coding assistants (e.g., Copilot) – an advantage
Familiarity with Graph Neural Networks (GNNs) – an advantage.
This position is open to all candidates.
