ADAS Vision Systems Engineer at Ford Global Career Site

Dearborn, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Jan, 26

Salary

0.0

Posted On

08 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ADAS, Camera Systems, Image Processing, Systems Engineering, Technical Direction, Cross-Functional Integration, Problem Solving, AI, Machine Learning, Data Analysis, Optics, Image Sensors, Sensor Fusion, Diagnostic Management, Requirements Management, Process Improvement

Industry

Motor Vehicle Manufacturing

Description

Camera System Architecture: Lead the definition, design, and evolution of the core ADAS camera system, creating requirements that produce robust and scalable hardware, software, and system designs. Advanced Technology Evaluation: Drive the research and evaluation of cutting-edge camera technologies (image sensors, optics, image processing pipelines, SoCs), recommending strategic improvements and robustness actions to significantly enhance camera system capabilities for advanced vision-based features. Technical Direction: Provide technical direction to engineering teams, ensuring regulatory compliance, performance targets (image quality, latency), and technical excellence. Ensure Cross-Functional Integration: Work closely with diverse internal teams (SW, HW, Validation, Perception, Fusion, Planning, etc.) and external partners to guarantee seamless integration, alignment, and robustness of ADAS camera system solutions. ADAS Strategic Alignment: Ensure the camera system architecture directly supports and aligns with critical ADAS strategic imperatives: Quality, Program Delivery, architecture evolution, vision-reliant L0-L3 features, AI/Data analysis needs, and simulation capabilities. Cross-Sensor Standardization: Drive initiatives to align and standardize camera system strategies and processes with those of other ADAS sensors, promoting consistency, efficiency, and robust system-level integration across the full sensor suite. Future Roadmap: Contribute to the long-term architectural roadmap for camera systems, considering evolving vehicle architectures and their impact on requirements, integration, and robustness. Systems Modeling & Documentation: Champion the use of structured system modeling tools (SysML/UML, e.g., Magic Draw) to accurately define, document, and analyze camera system architecture, requirements, and interfaces, thereby improving clarity and process efficiency. Process Improvement: Champion and drive continuous improvement in requirements management, systems engineering, and architectural development processes specifically tailored for ADAS camera systems. Complex Problem Resolution & Continuous Improvement: Drive the resolution of complex technical issues impacting ADAS camera system architecture, performance, calibration, and vehicle integration for both current and future programs. Leverage insights from these resolutions and lessons learned to inform the design of next-generation camera systems and prevent reoccurrence. Support the implementation and launch activities for current architectures. Diagnostic & Fault Management: Lead the definition and implementation of comprehensive diagnostic and fault handling strategies for the ADAS camera system, ensuring effective failure detection, reporting, and management spanning hardware, software interfaces, and the overall system. Established and active employee resource groups Bachelor's degree in Electrical Engineering, Mechanical Engineering, or Computer Science and a minimum of 6 years of relevant engineering experience. OR a minimum of 10 years of equivalent engineering experience without the specified degree. Knowledge of software, hardware, and systems development. Familiarity with overall vehicle Electrical/Electronic (E/E) architectures. Experience in roles such as automotive systems engineer, vehicle architecture implementation, or product launch within a sensor system development context. Experience working effectively in dynamic, cross-functional environments, including collaboration with internal and external partners. 5+ years of direct experience within the ADAS domain. Knowledge of ADAS software, hardware, and systems development, particularly in areas like camera perception, computer vision, or sensor fusion. Deep technical expertise in automotive camera systems, including a solid understanding of image sensors, optics, image processing pipelines (ISP), camera interfaces, and integration into vehicle Electrical/Electronic (E/E) architectures. Proven systems engineering experience, with a strong focus on automotive camera systems or embedded vision. Demonstrated ability to lead technical design reviews, discussions, and complex problem-solving sessions for ADAS systems. Experience with automotive (SAE L0-L3) features that heavily rely on camera input. Understanding of Artificial Intelligence (AI), Machine Learning (ML), or Data Analysis techniques applied to camera data. Excellent problem-solving skills, particularly for complex challenges related to advanced sensor system performance, quality, design, and integration. Strong communication skills (written and verbal) and effective collaboration abilities. Experience mentoring junior technical team members (formal or informal). Proven drive to exceed quality metrics.

Responsibilities

Lead the definition, design, and evolution of the core ADAS camera system while ensuring seamless integration with internal teams and external partners. Drive the research and evaluation of advanced camera technologies to enhance system capabilities for vision-based features.