Responsibilities
- Create scalable pipelines to ingest and process data streams into curated training datasets.
- Lead efforts to enhance data quality, detect anomalies, and handle out-of-distribution samples for reliable model training.
- Collaborate across autonomy and data infrastructure teams to deliver effective ML data solutions.
- Build tools and infrastructure that enable ML researchers to analyze data, find model weaknesses, and explore data distributions.
- Partner with data operations to define quality benchmarks, automate quality checks, and align annotations with model performance.
- Drive engineering initiatives to productionize active learning techniques developed in research.
- Develop systems for large-scale embedding computation, inference execution, vector database management, and smart data sampling for labeling.
Compensation
Base salary is part of a broader compensation package that may include bonuses, equity, and benefits.
Work Arrangement
Not specified
Other
- Base pay forms one component of the total compensation package.
- This role qualifies for an annual performance bonus, equity, and a comprehensive benefits offering.
- The company is committed to being an equal opportunity employer and strictly forbids workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or other legally protected traits.
