Serve Robotics is looking to build out a petabyte scale data platform supporting data partnerships, ML and autonomy engineers. This platform will directly impact a new revenue stream through commercialization of their robot data. The role will focus on building highly scalable data pipelines and improving data discoverability features, enabling the creation of diverse large scale datasets used to train cutting edge ML models for their fleet of robots.
Requirements
- Strong programming proficiency in Python, SQL
- Hands-on experience building and maintaining large-scale data processing pipelines using cloud technologies
- Proficiency with data warehousing and ETL/ELT concepts
- Solid understanding of system design, along with data privacy and security best practices
- Hands on experience setting up IaC to orchestrate cloud resources and security policies
- Experience with GCP and solid understanding of fully managed cloud infrastructure
- Familiarity with robotics data such as lidar, multi-modal camera, mapping, etc
Responsibilities
- Architect and implement robust, scalable data pipelines to process, synchronize, and package robotics data (e.g., LiDAR, camera, IMU, proprietary maps) for third-party consumption.
- Build a data processing and egress platform, ensuring the timely and accurate delivery of datasets according to strict partner SLAs.
- Create data lifecycle policies to control cloud data costs.
- Build and maintain a universal data catalogue of all raw robot data.
- Create cost monitoring, attribution and alerting systems.
- Build data discoverability platform features, use ml models to generate new attributes and maintain efficient, highly scalable search indexes.
- Setup data access audit trails and strong security controls managed through IaC.
Other
- 5+ years of professional experience in software or data engineering.
- Experience building and optimizing terabyte scale data pipelines
- Experience working in a fast paced startup environment
