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 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
Benefits
- Health and wellness: Comprehensive health insurance including medical, dental, vision, and disability coverage
- Life and family: Life and AD&D insurance and fertility benefits to ensure our team’s well-being and peace of mind
- Flexible vacation: We work hard but avoid burn out. Take time off when you need it
- Visa sponsorship: We support international talent with visa sponsorship to join our team
- 401(k) plan: Retirement savings plan to secure your financial future- 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
- Bachelor’s degree, or 4+ years of relevant experience in lieu of a degree
- 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
- Experience with SQL or other data analysis tools
- Comfort using AI agents, no/low-code tools, or light scripting (e.g., Python) to prototype workflows and measurement
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