ABOUT THE ROLE:

You will ensure engineering teams get the right data they need—high-quality tasks and evaluations—by crafting and executing high-value Human Data projects. You sit at the intersection of engineering and data operations: partnering with model teams, designing projects that capture meaningful signals, and driving data yield and eval lift. This is a hands-on technical role for engineers who deeply understand training and evaluation and want to influence data strategy.

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 yourself to continuously improve quality.
• Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy; prioritize 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.

BASIC QUALIFICATIONS:

• 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

PREFERRED SKILLS AND EXPERIENCE:

• Master’s degree or higher in a relevant technical field
• Direct experience curating, evaluating, or improving training or evaluation datasets for large language models or other AI/ML systems
• Experience designing, supporting, or optimizing annotation tools, labeling interfaces, or data workflows that prioritize factual accuracy and data integrity
• Familiarity with multimodal data (text + images, code, or other modalities) or domain-specific data (science, mathematics, programming, recent events, etc.)
• Experience conducting model or dataset evaluations focused on quality, truthfulness, or alignment with product goals
• Experience in a scripting language like Python
• Experience in SQL or other data analysis tools

ADDITIONAL REQUIREMENTS:

• Weekend work may be required.
• Travel to other SpaceXAI sites may be required.

COMPENSATION AND BENEFITS:

$144,000 - $270,000 USD

Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.