Engineer I - Software Algorithm

Magna International•Auburn Hills, MI

2d•Onsite

About The Position

The Computer Vision Algorithm Engineer role is focused on ADAS perception, transforming camera video feeds (image frames) into a clear understanding of the vehicle’s surroundings. The work spans concept through serial production, involving algorithm design and simulation, data analysis and replay, building and testing classical and deep learning models, and optimizing for real-time execution on production ECUs. Core tasks include object detection, segmentation, tracking, and image enhancement while meeting accuracy, latency, memory, and power targets. A strong background in image processing, machine learning, and mathematics/physics is required, with familiarity in vehicle dynamics considered a plus.

Requirements

Master’s degree in computer engineering, Software Engineering, Electrical Engineering, Computer Science, or equivalent.
Minimum of 3 years of experience in computer vision and image‑processing algorithm development using traditional methods and deep learning, with proven expertise in developing and implementing DNN models.
Excellent programming skills with C or C++; familiarity with Python with proficiency in deep learning frameworks (TensorFlow, PyTorch, Keras) is advantageous.
Strong grasp of machine learning concepts and neural network architectures (CNNs, RNNs, transformers).
Experience in image segmentation, object detection, and image data preparation/enhancement (e.g., normalization, augmentation, filtering, noise reduction, contrast adjustment, image restoration).
Experience in optimizing models for performance, including techniques such as quantization and distributed training.
Strong problem-solving abilities; capable of working independently and collaboratively; effective at communicating complex concepts to technical and non-technical audiences.
Strong foundations in mathematics and signal/image/video processing; computer vision fundamentals (object detection, tracking, feature extraction) with C/C++.
Experience developing AI and Machine Learning Algorithms for embedded devices.
Knowledge of automotive product development practices and structured engineering methodologies; development of portable, reusable, modular software for automotive systems.
Strong troubleshooting and debugging skills, using structured problem-solving methods (e.g., 8D).
Experience with disciplined software development processes (ASPICE or CMMI); configuration management; and project monitoring/control techniques.
Able to work effectively in a global environment
Able to represent technical topics internally and externally
Demonstrates self‑motivation, tenacity, and determination.
Able to work independently with minimal supervision.
Comprehensive knowledge of English (speak & write)

Nice To Haves

Familiarity in vehicle dynamics is considered a plus.
Experience with responsibilities listed above in the serial development of automotive electronics is preferred.

Responsibilities

Develop (design, implement, optimize) conventional image processing algorithms for automotive embedded serial production projects.
Design, develop/tune, and optimize deep learning models for ADAS computer vision features (e.g., pruning, quantization) and improve computational performance.
Plan and execute experiments to assess deep learning model effectiveness, compare architectures, and validate results through rigorous component/bench testing.
Analyze large datasets to extract insights, refine models, and improve overall performance and robustness.
Stay current with deep learning advances and incorporate innovative techniques and research findings into projects.
Collaborate with multidisciplinary (requirements, embedded, testing) teams to integrate models into existing systems and ensure seamless operation within the product ecosystem.
Document development processes, maintain detailed experiment logs, and present findings clearly to stakeholders.
Analyze defects and test results; perform root-cause analysis and implement algorithm improvements to achieve KPIs.
Independently deliver intermediate-to-advanced ADAS algorithm design, implementation, and testing.
Perform other duties in support of business objectives; maintain regular attendance; follow safe work procedures and PPE requirements; report hazards, injuries, and illnesses promptly; comply with Quality Operating System (QOS) and all safety regulations.