3 дня назад
ML Performance Optimization Engineer (Autonomous Driving)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Performance Optimization Engineer (Autonomous Driving) (GPU/NPU, C++/Python): Optimizing and deploying deep learning models for reliable, efficient operation on autonomous driving vehicle platforms with an accent on low-level CPU, GPU, and neural network accelerator performance. Focus on system profiling, automated performance analysis tools, model validation, and runtime optimization across vehicle environments.
Location: Hybrid role based in Pangyo (Software Dream Center), South Korea
Company
develops autonomous driving technologies and vehicle-based AI systems.
What you will do
- Optimize deep learning models using GPU and NPU acceleration for autonomous driving applications.
- Validate model performance and conduct system profiling across vehicle environments.
- Analyze and optimize CPU, GPU, and neural network accelerator performance.
- Develop and automate system performance analysis tools and evaluation metrics.
- Support AI model deployment and runtime optimization on vehicle platforms.
- Collaborate with AI model and software teams on performance validation and analysis.
Requirements
- Master’s degree or higher in artificial intelligence, machine learning, deep learning, or a related field, or equivalent practical experience.
- Strong understanding of machine learning and deep learning systems.
- Experience with low-level performance optimization for CPU, GPU, and NPU environments.
- Proficiency in C/C++, Python, and shell scripting.
- Development experience in Linux, QNX, or RTOS environments.
- Experience with system profiling and performance analysis.
Nice to have
- Experience optimizing machine learning workloads and linear algebra routines for deep learning systems.
- Experience optimizing image processing, computer vision, or robotics algorithms.
- Experience with CUDA, MKL, SIMD, or NEON optimization techniques.
- Experience developing or optimizing systems on NVIDIA-based vehicle platforms.
- Experience optimizing AI models for autonomous driving applications.
Culture & Benefits
- Collaboration with AI model and software engineering teams.
- Hybrid work arrangement.
- A 3-month probationary period may apply.
- Veterans, employment-protected applicants, and registered persons with disabilities receive preferential consideration in accordance with applicable laws.
Hiring process
- Application screening.
- First virtual interview, approximately 1 hour.
- Second interview, in person or virtual, approximately 3 hours, followed by offer discussion and onboarding.
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