Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Чётко описанная стажировка в крупной автомобильной технологической компании даёт практический опыт с LLM, RAG и формальной верификацией, хотя работа проходит на месте в Сингапуре, а условия наставничества не раскрыты.
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Передовые AI-задачиПонятные задачиКрупная компания
Оценка от Hirify AI
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Artificial Intelligence Intern (AI): Developing LLM-based solutions, RAG pipelines, and agentic AI workflows for automotive requirements engineering with an accent on requirement validation, formal methods, and model checking. Focus on designing experiments, synthesizing formal models and code, and evaluating AI solutions for complex engineering tasks.
Location: Singapore, Singapore
Company
hirify.global is an independent automotive technology and electronics company developing sensor solutions, displays, braking and comfort systems, software architecture platforms, and assistance systems for software-defined vehicles.
What you will do
Analyze and structure technical requirements from automotive OEMs.
Develop LLM-based solutions for requirement understanding, classification, and validation.
Build and evaluate RAG pipelines for engineering documents and domain knowledge.
Explore agentic AI workflows for complex engineering tasks.
Apply model checking and formal verification to validate system requirements and designs.
Design experiments, evaluate results, document findings, and collaborate with AI researchers, software engineers, and domain experts.
Requirements
Currently studying Computer Science, Artificial Intelligence, Software Engineering, Mathematics, Electrical Engineering, or a related field.
Basic knowledge of machine learning, natural language processing, or LLMs.
Programming experience in Python.
Interest in one or more of the following: LLMs and prompt engineering, AI agents, RAG and vector databases, formal methods and model checking, model synthesis and code generation, or automotive requirements engineering.
Nice to have
Experience with LLM frameworks such as LangChain, LlamaIndex, or similar.
Familiarity with formal verification tools or languages such as NuSMV, SPIN, UPPAAL, TLA+, or temporal logic.
Experience with embeddings, knowledge graphs, or document-processing pipelines.
Familiarity with Git, Docker, and software development practices.
Culture & Benefits
Opportunity to contribute to future mobility and software-defined vehicle technologies.
Collaboration with AI researchers, software engineers, and automotive domain experts.
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