Jobs at Seoul Robotics

Design and maintain Go backend services for autonomous driving operations, including event pipelines, RESTful APIs, real-time fleet-state streaming, PostgreSQL data management, migrations, and system instrumentation. Build resilient, fault-tolerant distributed services that relay commands between operators and the autonomy stack. Collaborate with engineering, QA, and operations teams while improving performance, observability, and reliability.

Seoul Robotics is recruiting 전문연구요원 (Specialized Research Personnel) for its autonomous robotics and AI/ML-focused organization. The posting highlights work in cutting-edge autonomous driving and robotics, an international English-speaking environment, flexible and hybrid work, and potential overseas opportunities. Applicants should contact the company to confirm eligibility and availability based on the enterprise research institute’s hiring capacity.

Build and improve autonomy software for planning, control, and estimation pipelines using Python and C++. Develop production-ready features, investigate issues through logs and simulation, improve reliability and performance, create testing and validation workflows, and participate in design and code reviews. The role involves translating operational needs into technical solutions and progressively owning software components in real-world autonomous vehicle systems.

Design and lead development of scalable, high-performance system software and middleware in Modern C++. Own core infrastructure (process management, resource isolation, runtime stability), implement fault detection and graceful degradation, build data pipeline/streaming for high-bandwidth sensors, profile and optimize CPU/GPU/memory/network, and mentor teams to enforce best practices and system interfaces.

Join the autonomous driving QA team to design and execute automated and manual tests across perception, prediction, planning, and control. Build CI/CD pipelines, expand simulated and real-world test coverage, analyze logs, reproduce defects, and improve QA processes to ensure safety, reliability, and performance of the driving stack.

Lead the design and implementation of high-performance perception architectures for autonomous driving, focusing on multi-sensor data fusion and deep learning optimization while mentoring junior engineers.

Design, implement, and productize high-performance 3D perception pipelines for autonomous systems. Lead multi-sensor fusion, optimize inference and hardware acceleration, mentor engineers, conduct code/design reviews, and collaborate cross-functionally to deliver robust production solutions.