Full-Stack SWE, Data Acquisition (Foundations)
Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams.
What this role actually needs.
Full-Stack SWE, Data Acquisition (Foundations) at OpenAI in San Francisco. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams.
Day-to-day expectations
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- Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards.
- Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management.
- Design and implement APIs to facilitate data interactions between internal services and external data sources.
- Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines.
- Optimize backend services for performance, scalability, and security in a distributed computing environment.
- Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices.
What a strong candidate brings
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- BS/MS/PhD in Computer Science or a related field.
- 4+ years of industry experience in full-stack development.
- Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go.
- Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL).
- Experience building data-intensive applications that handle large-scale datasets.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker).
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