AI Model Deployment EngineerXC-CP
AI Model Deployment EngineerXC-CP
Posted on :
14-02-2025
Employer Active
1 Vacancy
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Job Description
- Responsible for deploying AI models (such as E2E VLM BEV occupancy NLP etc.) converted from training frameworks into AI cockpit or autonomous driving products.
- Collaborate with algorithm team to support algorithm engineers in optimizing models including model compression quantization pruning distillation etc. to reduce model size and compute complexity.
- Collaborate with basic software team to optimize model design based on chip hardware resources and software architecture to ensure effective integration and performance of the algorithm in overall system.
- Research and evaluate different hardware platforms and software frameworks to select the best technical solution for different computing scenarios.
- Deploy model execution environments based on QNX/Linux/Android.
- Solve technical problems during AI model deployment including toolchains compilation integration and execution.
- Actively communicate with chip vendors to solve problems.
Qualifications :
- Bachelors degree or above in Computer Science Software Engineering Artificial Intelligence or electronic engineering field with solid knowledge in computer science.
- 3 years of experience in AI model deployment in autonomous driving or AI cockpits.
- Knowledgeable with common deep learning frameworks (such as PyTorch TensorFlow etc.) familiar with deep learning knowledge such as CNN and Transformer.
- Familiar with AI models for autonomous driving experience in deep learning model deployment and performance optimization is preferred.
- Familiar with Linux/QNX operating systems including task scheduling memory management etc.
- Proficient in C/Python programming languages.
- Proficient in crosscompilation integration development and debugging of embedded software SDKs.
- Familiar with heterogeneous computing with a deep understanding of computing resources such as CPU/DSP/GPU/NPU development and optimization of efficient communication and synchronization schemes and identification of chip computing bottlenecks.
- Experience in deploying models on edgeside AI chips is preferred such as Qualcomm SA8255/Nvidia Orin/Horizon J6 etc. Familiar with related technology stacks such as QNN/OpenCL/TensorRT/CUDA is preferred.
- No block on reading English specification and technical documents good oral English is a plus.
- Strong ability to learn quickly strong selfmotivation and enjoy sharing and helping others.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
Key Skills
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