Job Details

We bring innovative vehicle features to life. Ford's Advanced Driver Assistance Software and Feature Development team is at the forefront of designing and developing next-generation features that enhance the driving experience, safety, and aesthetics of our vehicles. This feature development team focuses on creating innovative solutions from early concept development through production launch.

We are seeking professionals with a passion for bringing cutting-edge ideas to life who can contribute to our efforts in the development of new Driver Assistance Multi-Feature Threat Assessment (MTA) functions for ADAS features.

The Feature Developer/Model-Based Software Engineer for Multi-Feature Threat Assessment functions will be responsible for developing robust functional algorithm models and software. This role specifically focuses on model-based software development, integration, and verification/simulation for advanced radar object perception and multi-feature threat assessment functions.

What you'll do...

• Design, develop, and deliver Matlab/Simulink models and associated autocode for Driver Assistance Multi-Feature Threat Assessment (MTA) functions for ADAS Features. Ensure these models meet feature-level requirements and integrate seamlessly with other Feature Software Components within the production embedded software environment.

• Responsible for creating detailed implementation requirements, unit test cases, and functional test cases.

• Collaborate with cross-functional teams including feature development, feature systems, verification & validation, platform systems and software, hardware, functional safety, customer experience, and attribute engineers to deliver concept and production-level software for Driver Assistance MTA functions.

• Develop and execute unit and functional test cases for Model-in-the-Loop (MIL) / Software-in-the-Loop (SIL) verification of Driver Assistance MTA functions and their models, evaluating behavior and impact on customer experience.

• Closely coordinate with feature development engineers to support execution of design verification plans (DVPs) to ensure proper performance of Driver Assistance MTA functions.

• Support data replay, resimulation, and bench testing.

• Ensure functions are properly delivered to meet software quality assurance standards and program timing.

• Work with the software team to integrate and autocode the Driver Assistance MTA function models for production software.

• Support the validation of interfacing system/function models.

• Work with tool developers to integrate functions in larger co-simulation and ECU simulation environments.

• Collaborate with the feature systems team, hardware-in-the-loop, simulation, and vehicle test teams to establish replay and re-simulation procedures.

You'll have...

• Bachelor's degree in Electrical Engineering, Computer Science, Mechanical Engineering, Systems Engineering, or a related field. Engineering Master's degree preferred.

• 10+ years' experience with software development using MathWorks toolchain (Matlab / Simulink / Stateflow) in automotive embedded systems or similar complex electromechanical systems.

Even better, you may have...

• Demonstrated foundational understanding and project experience related to:

  1. Algorithmic Proficiency:

  2. Designing, developing, and optimizing algorithms for:

  3. Lane Violation: Assessing threats in adjacent lanes, including headway calculation and predictive analysis for lane changes.

  4. Reference Line Analysis: Interpreting object motion relative to defined longitudinal and lateral reference lines for proximity and potential collision.

  5. Intrusion of Path: Predicting intersections of object and host vehicle trajectories.

  6. Strong background in signal processing and data fusion from various sensors (e.g., radar, lidar, cameras), as well as down-selection algorithms, including expertise in the Traffic Participant Selection (TPS) component.

  7. In-depth knowledge of automotive coordinate systems, specifically adherence to standards for vehicle axes (x-front, y-left, z-up), and understanding of vehicle dynamics (e.g., roll, pitch, yaw, deceleration, gaps).

  8. Experience with configurable algorithms and parameter tuning for different modes (e.g., Normal, Cautious, Aggressive) to balance safety and performance characteristics.

  9. Proficiency in the full software development lifecycle (requirements analysis, design, implementation, testing, deployment) within an automotive context.

  10. Automotive & ADAS Domain Knowledge:

  11. Comprehensive knowledge of ADAS Features.

  12. Ability to define and classify threats, including various vehicle types (cars, trucks, motorcycles, bicycles) within the driving path and vicinity.

  13. Understanding of ADAS system architectures, including how sensors, processing units, and control algorithms integrate.

  14. General understanding of ISO26262 Functional Safety and Automotive Safety Integrity Levels (ASIL), as well as an understanding of different levels of driving automation (e.g., SAE).

  15. Experience with real-time processing and low-latency data handling, as required for ADAS applications.

  16. Software Engineering & Development Process:

  17. Model-Based Design (MBD): Extensive experience with MBD development processes, including proficiency in Simulink for algorithm design and implementation.

  18. Embedded Software Development: Strong background in developing software for embedded automotive systems, with a focus on real-time constraints, CPU load, RAM/ROM optimization, and fixed-rate execution (e.g., 25 ms cycle time).

  19. Version Control & Documentation: Proficiency with version control systems like Git and experience using tools for interface definitions and data dictionaries (e.g., AIMdb).

  20. Requirements Management: Strong background in writing detailed and level-appropriate requirements (e.g., Software-Level Requirements), including familiarity with ASPICE Traceability Model and requirements management tools like Jama.

  21. Fault Handling & Diagnostics: Understanding of fault handling strategies in ADAS, including reliance on common software components for fault detection, processing "Suppress" or "Deny" requests, and providing feature-specific diagnostic issue codes (DIDs).

  22. Testing, Debugging & Quality Assurance:

  23. Comprehensive Testing Strategies: Experience in defining and executing various testing methodologies, including Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), Rapid Control Prototyping (RCP), Hardware-in-the-Loop (HIL), and in-vehicle testing.

  24. Test Case Development: Ability to design and implement integration tests, ensuring comprehensive coverage of software component inputs, outputs, and interactions with other modules.

  25. Debugging & Analysis: Expertise in debugging embedded software using dedicated tools, debug streams (e.g., UDP, XCP), and A2L files for signal logging and analysis.

  26. Quality Assurance: Commitment to ensuring software quality through adherence to coding guidelines (e.g., Modeling Guidelines), regular performance analysis, and addressing identified risks.

  27. Collaboration & Project Management:

  28. Cross-functional Collaboration: Excellent communication and teamwork skills to collaborate effectively with various internal and external stakeholders, including global development teams, sensor teams, hardware teams, and project managers.

  29. Technical Leadership & Ownership: Demonstrated ability to take full ownership of a complex software component, guiding its development from high-level design through implementation, testing, and maintenance.

  30. Team Leadership & Guidance: Demonstrated ability to lead a small team of colleagues and purchased services to deliver against program timings and software release schedules, coordinating individual skill sets with the required tasks. Where