3 часа назад
Software Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer (AI): Building automation tools and AI-powered internal solutions to improve engineering productivity and support mass production of autonomous driving systems with an accent on workflow orchestration, issue diagnosis, and large-scale software deployment. Focus on developing LLM- and agent-based solutions, solving complex system issues, and driving reliable production delivery through cross-functional collaboration.
Location: Beijing, China; on-site
Company
develops autonomous driving technologies and systems.
What you will do
- Identify engineering productivity bottlenecks in the mass production of autonomous driving systems and crowdsourced mapping algorithm models.
- Design and develop automation tools for issue diagnosis, workflow orchestration, and large-scale software deployment.
- Build AI-, LLM-, and agent-based internal solutions to address practical engineering problems.
- Investigate complex system issues and continuously improve automation tools based on real production needs.
- Collaborate with local algorithm R&D, validation, testing, and global R&D teams to align requirements and support reliable production delivery.
Requirements
- Master’s degree in Computer Science, Software Engineering, or a related field.
- Strong Python programming skills and proficiency in at least one system language: C++, Rust, or Java.
- 3–5 years of experience building software tools, automation solutions, backend services, or AI-powered solutions.
- Strong analytical and problem-solving skills.
- Ability to collaborate effectively in cross-functional engineering environments.
- Fluent Mandarin and working-level English are required.
Nice to have
- Experience with LLMs, AI-assisted development tools, or agent frameworks.
- Background in machine learning or algorithm development.
Culture & Benefits
- On-site work within an R&D algorithms organization.
- Close collaboration with local and global engineering teams.
- Focus on practical automation, AI-powered efficiency improvements, and reliable production delivery.
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