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- Data Closed-Loop Engineer
JOB ID 28256
Data Closed-Loop Engineer
- Manufacturer, Manufacturer-Automotive
- IT, Data Analyst, Network, Infrastructure engineer, Product Engineer (Hard/soft)
- Tokyo
- ¥10,000,000～¥20,000,000
A Japanese deep tech startup founded in April 2024. Specializing in the development of autonomous driving systems for large trucks, it aims to solve challenges faced by Japan's logistics industry, such as driver shortages, aging populations, and increasing logistics demand. Focusing on trunk line transportation using expressways, it promotes improved transport safety, operational efficiency, and reduced logistics costs through advanced AI-powered autonomous driving technologies. Through collaboration with automakers and logistics companies, it is working on the practical use of autonomous trucks and the construction of next-generation logistics infrastructure.
A Japanese deep-tech startup established in April 2024, specializing in the development of autonomous driving systems for heavy-duty trucks. The company aims to transform Japan’s logistics industry by addressing challenges such as driver shortages, an aging workforce, and increasing freight transportation demand. Focusing on autonomous highway transportation, it develops advanced AI-powered technologies designed to improve transportation safety, operational efficiency, and logistics sustainability. Through collaboration with automotive manufacturers and logistics companies, the company is working toward the commercialization of autonomous trucking solutions and the development of next-generation automated freight transportation infrastructure in Japan.
Build the data infrastructure that directly determines how fast our autonomous driving models improve. You'll own backend platform capabilities across the full data closed loop—sensor ingestion, scene mining, dataset management, cloud-scale simulation, and evaluation—so that algorithm teams can iterate faster on better data.
Job Description
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- Responsibilities
- ・Build and maintain core backend services for the data closed-loop platform, spanning data ingestion, scene mining, dataset management, and evaluation; own modules end-to-end from design to production
・Design and implement high-performance data processing pipelines for raw sensor logs (LiDAR / Camera / Radar), supporting large-scale batch and streaming workloads with reliable throughput
・Build scene mining and active learning capabilities—anomaly detection, trigger-based recall, and semantic search—to continuously surface high-value data
・Build the backend infrastructure for cloud-scale parallel simulation testing: job scheduling, scene library management, and results evaluation pipeline, automating the full loop from road-test data to simulation validation to model iteration
・Own the data storage and versioning architecture; ensure training data is traceable and reproducible with robust lineage and quality governance
・Deliver data services for algorithm teams—scene retrieval APIs, dataset publishing, DataLoader interfaces—and continuously reduce the time from road test to usable training set
・Participate in architecture reviews and technology decisions; collaborate with algorithm, annotation, and simulation teams to drive iterative improvement
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- Requirements
- ・Bachelor's degree or above in CS or a related field; 3+ years of backend engineering experience in data platforms or autonomous driving data closed-loop systems
・Proficiency in Python, Go, or Java; solid system-level design skills with a strong emphasis on production code quality
・Hands-on production experience with distributed computing frameworks (Spark, Ray, or Flink); able to identify and resolve performance issues at scale
・Experience with data versioning or Lakehouse architecture (Iceberg, Hudi, or Delta Lake), or platform-level dataset lineage systems
・Practical experience with workflow orchestration tools (Airflow, Dagster, or Argo)
・Clear understanding of the autonomous driving data closed-loop flow; able to communicate directly with algorithm engineers
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- Preferred
- ・Experience building backend infrastructure for cloud-scale simulation platforms (job scheduling, scene management, results pipeline)
・Led a data platform build from scratch (0 to 1)
・Production experience with commercial or passenger vehicle autonomous driving data closed loops
・Engineering experience with vector search, active learning, or VLM-assisted annotation pipelines
・Kubernetes experience; PB-scale object storage or cloud-native data platform development
・Actively uses AI coding tools (LLM/Copilot) as part of daily engineering workflow
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- Location
- Tokyo
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- Work Style
- Remote working possible, Flex working possible
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- Salary
- ¥10,000,000～¥20,000,000
-
- Attractive
Points - Japanese company with global opportunities, Weekends and holidays off, Major corporation
- Attractive
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