Human Data Manager

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 model teams and data operations: partnering with engineering, designing projects that capture meaningful signals, and driving measurement of data impact. This is a hands-on role for people who understand training and evaluation deeply and want to influence data strategy.

• →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 evaluation projects that capture meaningful training signals and support rapid model development.
• →Leverage AI agents and existing platforms to measure data effectiveness and quantify impact (data yield, eval lift, usage).
• →Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy; prioritize quality over quantity.
• →Research and apply techniques for data collection, annotation, generation, and multi-modal integration.
• →Shape Grok’s behavior and domain performance through targeted data work; improve annotation workflows using agents and no/low-code approaches where helpful.
• →Manage plans that shape model behavior via data management, optimization, and analysis, including resources and timelines.
• →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.

• Bachelor’s degree, or 4+ years of relevant 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

• Degree in engineering, computer science, data analysis, or a related STEM discipline (Bachelor’s or higher)
• 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 workflows or data processes 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 with model or dataset evaluations focused on quality, truthfulness, or alignment with product goals
• Comfort using AI agents, no/low-code tools, or light scripting (e.g., Python) to prototype workflows and measurement
• Experience with SQL or other data analysis tools

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