Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Понятные задачи для стажёра сочетают оптимизацию AI-моделей и низкоуровневую работу с аппаратной частью, что даёт ценный опыт в специализации; зарплата не указана, поэтому условия оплаты остаются неизвестными.
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Зарплата не указанаПонятные задачиАктуальный стекAI на устройствеВысокий темп
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Software Engineer Intern (AI): Developing software and tools for training, optimizing, and deploying AI models on Ambarella AI SoCs with an accent on heterogeneous computing, memory hierarchies, and hardware–software integration. Focus on implementing state-of-the-art techniques, optimizing AI workloads across specialized processors, and solving performance challenges on edge platforms.
Location: US Headquarters
Company
hirify.global develops AI vision processors and solutions for edge applications that extract data from high-resolution video streams.
What you will do
Develop software and tools for training, optimizing, and deploying AI models on hirify.global AI SoCs.
Analyze AI workloads and optimize performance across heterogeneous compute engines and memory hierarchies.
Study research papers and implement state-of-the-art techniques to solve technical challenges.
Collaborate with software and hardware engineers and cross-functional teams to deliver optimized solutions.
Requirements
Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Strong programming skills in C/C++ and Python.
Basic understanding of computer architecture, microprocessors, and memory systems.
Strong problem-solving and analytical skills.
Effective communication skills and the ability to work well in a collaborative team environment.
Interest in understanding how software interacts with and leverages hardware.
Nice to have
Familiarity with AI SoCs, CPUs, GPUs, NPUs, or other AI accelerators.
Experience developing software for edge AI embedded systems.
Knowledge of deep learning or computer vision fundamentals.
Understanding of AI workloads such as CNNs, LLMs, or VLMs.
Experience with deep learning frameworks such as PyTorch or TensorFlow.
Culture & Benefits
Hands-on work at the hardware–software boundary across AI workloads, system software, performance optimization, and specialized hardware.
Collaboration with engineers across hardware and software disciplines.
Fast-paced environment involving challenges across different system layers.
Opportunities to learn new technologies and solve technical and performance problems.
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