ADAS Algorithm Engineer (Perception)

Job Title

Developer – Situation Interpretation & Collision Threat Assessment for ADAS

Role Overview

We are looking for an experienced C++ Developer to join the ADAS/Automated Driving software development team, focusing on situation interpretation, environment understanding, and collision threat assessment.

The role involves developing and integrating software components that interpret information from vehicle sensors and perception systems, understand the surrounding driving situation, and assess potential collision risks and threats for advanced driver assistance functions like front and rear collision avoidance systems.

The ideal candidate will have strong expertise in modern C++ development, automotive software engineering, ADAS/AD concepts, and experience working with the Automotive SW development experience ecosystem. Experience with perception, object tracking, prediction, risk assessment is highly desirable.

Key Responsibilities

• Develop and maintain C++ software components for situation interpretation and collision threat assessment in ADAS/AD systems.

• Implement algorithms to analyse the vehicle's surrounding environment and identify potential collision scenarios and safety-critical situations.

• Process and interpret inputs from perception and sensor-fusion components, including:

• Object lists

• Object classification

• Object tracking

• Object positions and velocities

• Lane and road information

• Ego-vehicle state

• Traffic/environment information

• Develop algorithms for collision risk assessment, including:

• Time-to-Collision (TTC)

• Time-to-React / Time-to-Impact concepts

• Relative distance and velocity analysis

• Collision probability/risk estimation

• Path/lane conflict assessment

• Cut-in, cut-out, crossing and merging scenarios

• Contribute to situation interpretation and scene understanding, transforming low-level perception information into meaningful driving situations.

• Develop and maintain software for detecting and evaluating dynamic and static obstacles and their potential interaction with the ego vehicle.

• Support the definition and implementation of ADAS safety-relevant use cases and functional requirements.

• Integrate software components within the development environment.

• Work closely with teams responsible for:

• Perception

• Sensor Fusion

• Object Tracking

• Prediction

• Motion Planning

• System Engineering

• Verification & Validation

• Perform software design, implementation, debugging, unit testing, and integration testing.

• Analyze simulation and vehicle-test data & traces to identify false positives, false negatives, and corner cases in collision-threat assessment.

• Support SIL/MIL/HIL and vehicle-level testing of ADAS functions.

• Participate in code reviews and ensure compliance with automotive software development standards and coding guidelines.

• Contribute to continuous improvement of algorithms, software architecture, performance, robustness, and maintainability.

Required Technical Skills

C++ / Software Development

• Strong hands-on experience with C++17/C++20 or equivalent modern C++.

• Strong understanding of:

• Object-oriented programming

• STL

• Templates

• Smart pointers

• Multithreading/concurrency

• Memory management

• Exception handling

• Design patterns

• Experience developing real-time and performance-critical software.

• Good knowledge of software development, debugging, profiling, and optimization.

• Experience with Git and modern CI/CD development environments.

Strong understanding of one or more of the following:

• Environment perception
• Object detection and tracking
• Sensor fusion
• Situation interpretation
• Scene understanding
• Object prediction
• Collision avoidance
• Collision threat assessment
• Lane/road model interpretation

Hands-on knowledge of concepts such as:

• Time-to-Collision (TTC)
• Relative position, velocity and acceleration
• Longitudinal and lateral collision risk
• Object trajectory intersection
• Predicted collision point
• Collision probability
• Safe distance / safety margins
• Cut-in and crossing-object scenarios
• Pedestrian and cyclist interaction
• Vehicle-to-vehicle and vehicle-to-object collision scenarios
• False-positive and false-negative analysis
• Edge-case and corner-case handling

Testing & Validation

• Experience with unit testing and integration testing of C++ software.
• Familiarity with frameworks such as Google Test/Google Mock.
• Experience with simulation-based validation of ADAS functions.
• Ability to analyze recorded sensor/perception data and vehicle logs.
• Experience with SIL, MIL, HIL, or vehicle testing.
• Knowledge of scenario-based testing and automated test execution is a plus.
• Familiarity with tools for trace analysis and KPI tracking.

Soft Skills

• Strong analytical and problem-solving skills.
• Ability to understand complex vehicle/environment interactions.
• Strong debugging and root-cause-analysis capabilities.
• Good communication and collaboration skills.
• Ability to work effectively in a multidisciplinary team.
• Strong ownership and commitment to software quality.
• Ability to work in an agile development environment.
• Comfortable working with safety-critical and quality-sensitive automotive software.

Nice-to-Have Skills

• Experience with ADAS Level 2/Level 2+ or higher automation functions.
• Experience with ACC, AEB, FCW, LKA/LCC, emergency maneuvering, or collision avoidance functions.
• Experience with vehicle trajectory prediction.
• Knowledge of probabilistic methods and uncertainty handling.
• Knowledge of machine-learning-based perception systems and their interfaces.
• Python scripting for test automation and data analysis.
• Experience with large-scale automotive software platforms.

Key Competencies

Must Have:

• Modern C++
• Automotive software development
• ADAS/Automated Driving fundamentals
• Situation interpretation / environment understanding & modelling
• Collision threat assessment
• Git and software development best practices
• Unit/integration testing
• Trace analysis and data pattern recognition for KPI tracking

Good to Have:

• Sensor fusion
• Object tracking and prediction
• ASPICE
• SIL/HIL/vehicle testing/ trace analysis