Human Data - Engineer
$144k - $220k • Palo Alto, CA
Posted 7d ago
Remote Work Policy
On-site
Categories
LLM Engineer
About the job
SpaceXSI is building Super Intelligence to help humanity understand the universe, developing the full Super Intelligence stack from supercomputers to large language models and applications. This role is at the intersection of engineering and data operations, focusing on ensuring engineering teams receive high-quality data for training and evaluation. You will partner with model teams, design projects to capture meaningful signals, and drive data yield and evaluation lift, influencing data strategy through hands-on technical work.
Responsibilities
- Partner with model and engineering teams to understand needs and translate them into high-value data projects and evaluation strategies.
- Own end-to-end delivery of critical data and eval projects that capture meaningful training signals and support rapid model development.
- Build tools and systems to measure data effectiveness (data yield, eval lift, usage), and run evaluations to continuously improve quality.
- Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy, prioritizing quality over quantity.
- Research, implement, and evaluate techniques for data collection, annotation, generation, and multi-modal integration.
- Shape Grok’s behavior and domain performance through targeted data work.
- Design and improve annotation workflows, labeling interfaces, and related tools with a focus on data quality and integrity.
- Act as a liaison between engineering, technical staff, and tutoring / Human Data teams to drive alignment and knowledge sharing.
- Collaborate with Human Data Ops and stakeholders to scale projects, share learnings, and contribute to demand forecasting; report status, insights, and blockers for rapid decisions.
Requirements
- Bachelor’s degree in engineering, computer science, or a related STEM discipline, or 4+ years of experience in lieu of a degree.
- Experience collaborating with cross-functional teams (engineering, research, product, or annotation/operations groups).
- Demonstrated experience analyzing datasets to identify trends, anomalies, quality issues, or integrity problems.
- Master’s degree or higher in a relevant technical field (preferred).
- Direct experience curating, evaluating, or improving training or evaluation datasets for large language models or other AI/ML systems (preferred).
- Experience designing, supporting, or optimizing annotation tools, labeling interfaces, or data workflows that prioritize factual accuracy and data integrity (preferred).
- Familiarity with multimodal data (text + images, code, or other modalities) or domain-specific data (science, mathematics, programming, recent events, etc.) (preferred).
- Experience conducting model or dataset evaluations focused on quality, truthfulness, or alignment with product goals (preferred).
- Experience in a scripting language like Python (preferred).
- Experience in SQL or other data analysis tools (preferred).
Benefits
- Equity
- Comprehensive medical, vision, and dental coverage
- Access to a 401(k) retirement plan
- Short & long-term disability insurance
- Life insurance
- Various other discounts and perks