Tasks:
- * Build data feedback loops for training, evaluation, simulation, and robot execution
- * Build multimodal data processing platform
- * Develop data collection, cleaning, annotation, and quality-control pipelines
- * Implement data lineage and reproducible training data delivery
- * Manage dataset construction, versioning, and metadata
- * Optimize platform performance, reliability, access control, and cost
Perks/Benefits:
Skills/Tech stack required:
[Airflow] [Annotation quality control] [ClickHouse] [Data Annotation] [Data Annotation Quality] [Data annotation quality control] [Database systems] [Data cleaning] [Data Lakes] [Data Lineage] [Data Processing] [Dataset versioning] [Data Warehouses] [Distributed data] [Distributed data processing] [Docker] [Elasticsearch] [Flink] [Go] [Hadoop] [Hive] [Java] [Kafka] [Kubernetes] [Message Queues] [Multimodal Data] [Object storage] [Python] [Quality Control] [Ray] [Robot data] [Scala] [Spark] [Task Scheduling]
Educational requirements:
[Bachelor's Degree]
Role(s):
[Data Engineer] [Data Platform] [Data Platform Engineer] [Engineer] [Platform Engineer]