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What we offer:At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.Group Summary:Transforming mobility. Making automotive technology that is smarter, cleaner, safer and lighter. That’s what we’re passionate about at Magna Electronics, and we do it by creating world-class Electronic systems. We are a premier supplier for the global automotive industry with full capabilities in design, development, testing and manufacturing of complex Electronic systems. Our name stands for quality, environmental consciousness, and safety. Innovation is what drives us and we drive innovation. Dream big and create the future of mobility at Magna Electronics.

Job Responsibilities:

MISSION:
To drive the deployment and acceleration of perception algorithms onto embedded platforms for mass-production ADAS/autonomous driving systems. The role requires exceptional C++ and CUDA programming skills to optimize, port, and deploy deep learning models using TensorRT, with a strong focus on production-level efficiency and reliability. And being able to deploy accelerated models in Axera or  horizons robotics chips. The engineer will be responsible for operator rewriting, algorithm acceleration, and ensuring seamless performance on target hardware.

POSITION RESPONSIBILITY:
•  Develop, optimize, and deploy perception algorithms (e.g., detection, segmentation) onto embedded platforms for ADAS/autonomous driving applications. 

•  Perform operator rewriting and kernel-level optimization using C++/CUDA to maximize inference performance on target hardware. 

•  Utilize TensorRT for model quantization, compilation, and deployment, ensuring optimal latency and accuracy. 

•  Collaborate closely with foreign-based algorithm and software teams to understand requirements, discuss technical solutions, and integrate modules. 

•  Lead the on-board deployment of perception models, including performance profiling, bottleneck analysis, and cross-platform optimization. 

•  Drive projects from R&D to mass production (SOP), ensuring robustness, efficiency, and compliance with automotive standards. 

•  Support the integration and acceleration of models on specific AI chips, leveraging expertise in platforms such as Horizon Robotics or Axera.

POSITION REQUIREMENTS:
REQUIRED QUALIFICATIONS

•  Master's or PhD in Computer Science, Electrical Engineering, Robotics, or a related field. 

•  Minimum of 3+ years of hands-on experience in C++ development within ADAS, autonomous driving, or embedded AI. 

•  Proven track record of deploying deep learning models to real-world products, with at least one successful mass-production project. 

•  Strong communication skills in English, capable of clear and effective technical discussions with foreign colleagues and partners. 

•  Deep understanding of computer vision and deep learning fundamentals. 

•  A problem-solving mindset, a strong sense of ownership, and the ability to work independently in a fast-paced environment.

TECHNICAL SKILLS REQUIREMENTS
•    Core Languages & Frameworks: 
o    Expert-level C++ programming in a Linux development environment. 
o    Advanced CUDA programming and performance profiling (Nsight). 
o    Proficient in Python for scripting and model conversion (PyTorch, TensorFlow). 
o    Extensive experience with NVIDIA TensorRT for model optimization and deployment. 
•    Domain Knowledge: 
o    In-depth knowledge of deep learning model deployment pipelines and optimization techniques (pruning, quantization, knowledge distillation). 
o    Solid understanding of computer vision tasks relevant to ADAS, such as object detection, semantic segmentation, and depth estimation. 
•    Platform & Hardware Expertise: 
o    Strong Preference: Practical working experience with AI chips from Horizon Robotics (Journey series) or Axera (Axera Tech). 
o    Experience with operator development, custom layer implementation, and model migration for specific AI accelerators. 
o    Familiarity with embedded system development and optimization. 
•    Core Competencies: 
o    Algorithm acceleration and low-level optimization skills. 
o    Experience in rewriting or implementing custom operators for unsupported layers. 
o    Strong analytical skills for performance profiling and bottleneck identification.

Awareness, Unity, Empowerment:

At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.

Notice regarding the use of AI:

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system.

These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team.

Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.

Worker Type:

Regular / Permanent

Group:

Magna Electronics