Role overview
- Have industry experience as a Data Engineer, Machine Learning Engineer, or Data Scientist; you are comfortable with large amounts of data.
- Own problems end-to-end, and are willing to pick up whatever context is needed to get the job done.
- You enjoy working as part of a fast-moving team.
- A desire to dig into problems across the stack, whether networking issues, performance bottlenecks, memory leaks, or simply reading unfamiliar code to figure out where potential issues might exist.
- Have a strong belief in the crucial need of high-quality data for producing state-of-the-art machine learning systems.
What you'll work on
- Design data pipelines for large scale data ingestion. This includes figuring out ways to store and process the data with robust features for filtering, pre-processing, and versioning.
- Build and refine custom data labeling services that directly influence the quality of our ML models.
- Work closely with other internal stakeholders to incorporate their data usage needs.
- Improve our data quality by deploying techniques like semi-supervised learning, human-in-the-loop machine learning, and fine-tuning with human feedback.
Tags & focus areas
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