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Job description
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TL;DR
Human Data Engineer (AI): Designing and delivering high-value human data projects, evaluation strategies, and annotation systems for AI model development with an accent on data quality, truthfulness, and measurable evaluation impact. Focus on building data-effectiveness tools, improving multimodal collection workflows, and shaping model behavior through rigorous training and evaluation data.
Location: Palo Alto, California, United States. Weekend work and travel to other sites may be required.
Salary: $144,000–$270,000 USD
Company
AI research and product organization developing systems designed to understand the universe and support human knowledge.
What you will do
- Partner with model and engineering teams to translate technical needs into data projects and evaluation strategies.
- Own end-to-end delivery of training-data and evaluation initiatives that capture meaningful signals for rapid model development.
- Build measurement tools for data yield, evaluation lift, usage, and overall data effectiveness.
- Research and evaluate data collection, annotation, generation, and multimodal integration techniques.
- Design annotation workflows, labeling interfaces, and supporting tools focused on factual accuracy and data integrity.
- Coordinate with engineering, technical staff, Human Data Operations, and tutoring teams to scale projects and share insights.
Requirements
- Bachelor’s degree in engineering, computer science, or a related STEM discipline, or 4+ years of equivalent experience.
- Experience collaborating across engineering, research, product, annotation, or operations teams.
- Experience analyzing datasets to identify trends, anomalies, quality issues, or integrity problems.
- Experience with Python or another scripting language.
- Experience with SQL or other data-analysis tools.
- Availability for possible weekend work and travel to other company sites.
Nice to have
- Master’s degree or higher in a relevant technical field.
- Experience curating, evaluating, or improving datasets for large language models or other AI/ML systems.
- Experience optimizing annotation tools, labeling interfaces, or data workflows.
- Familiarity with multimodal or domain-specific data, including science, mathematics, programming, or current events.
- Experience evaluating model or dataset quality, truthfulness, or alignment with product goals.
Culture & Benefits
- Small, highly motivated team focused on engineering excellence and curiosity.
- Flat structure with hands-on contribution expected across the organization.
- Equity as part of the total rewards package.
- Medical, vision, and dental coverage.
- 401(k), disability insurance, life insurance, discounts, and additional perks.
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