AI Agent Data Pipeline Intern
- Build pipelines to ingest and organize experiment-related data from team communications, meeting notes, experiment plans, analysis documents, metrics, and evaluation results.
- Use LLM-based methods to clean noisy unstructured data, extract experiment-relevant information, and convert fragmented discussions into structured records.
- Design data schemas, metadata, and quality checks that make experiment context easier to search, trace, and use in downstream agent workflows.
- Support retrieval and indexing workflows, including semantic search or RAG-style pipelines, so the agent can access relevant experiment context.
- Prepare curated datasets for agent evaluation and, where applicable, LLM fine-tuning or instruction-tuning.
- Work with MLEs and platform engineers to understand experiment workflows, data gaps, and the types of insights most useful for planning and analysis.
- Evaluate whether the agent uses curated experiment data correctly to generate summaries, comparisons, recommendations, and analysis insights.
- Contribute to internal tools, dashboards, or reports that help teams monitor experiment status, outcomes, and trends.
- Strong skills in Python, SQL, and data processing.
- Experience working with structured and unstructured data, including text-heavy sources such as documents, notes, messages, or logs.
- Familiarity with data pipelines, ETL workflows, or large-scale data processing.
- Interest in LLM development, LLM evaluation, agentic AI systems, RAG pipelines, semantic retrieval, prompt engineering, or LLM-assisted data processing.
- Familiarity with machine learning workflows, model training, evaluation metrics, or MLOps concepts.
- Strong analytical thinking and attention to data quality, consistency, and reliability.
- Comfort working with ambiguous data sources and collaborating with ML and platform engineers to clarify requirements.
- Previous experience building internal tools, automation scripts, or data quality checks.
- A fun, supportive and engaging environment.
- Infrastructures and computational resources to support your work.
- Opportunity to work on cutting edge technologies with the top talents in the field.
- Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
- Competitive compensation package.
- Snacks, lunches, dinners, and fun activities.
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