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Turing is a research accelerator for frontier AI labs and enterprise AI deployment, partnering with leading LLM research teams to build high-quality training datasets at scale. The Client Director, Frontier Data role is a strategic operational leadership position responsible for driving large-scale LLM training program development and execution.
Key responsibilities include leading and scaling global delivery teams of 100+ people across functions, regions, and levels (individual contributors, leads, and managers). You will implement data-driven performance management systems that measure productivity, quality, and output consistency, building operational structures that ensure transparency and accountability. You'll own the quality, accuracy, and scalability of datasets generated for LLM training, moving beyond manual QA by leveraging Python scripting, APIs, and automation frameworks to validate and improve dataset integrity. This includes designing tools and scripts for data validation, annotation accuracy checks, and pipeline consistency while ensuring compliance with PII, GDPR, and HIPAA standards.
You will lead the generation and delivery of high-quality, scalable datasets focused on supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), reasoning, and agentic workflows. This includes overseeing the entire data lifecycle from client intake and annotation workflow design through delivery, and partnering with product, research, and engineering teams to implement evaluation metrics such as win rate, inter-annotator agreement, and pairwise preference scoring.
As the primary point of contact for enterprise AI clients, you'll manage expectations, delivery timelines, and escalations while building relationships with engineering and research stakeholders. You'll communicate effectively across technical and non-technical audiences, providing transparency through structured updates and quality reporting. Additionally, you'll recruit, mentor, and coach cross-functional leaders in engineering, data, operations, and program management, driving adoption of internal tools and championing continuous improvement across data quality, tools, and delivery processes.
Required qualifications include 10+ years of experience leading large-scale technical delivery organizations, ideally in AI, ML, or data operations; a Bachelor's degree in Engineering, Computer Science, or equivalent technical discipline; demonstrated ability to act as a strategic business partner with clients, researchers, and engineers at leading LLM labs; proven success building and scaling multi-level high-performance teams with distributed global operations, including experience managing managers and skip-level performance management; and hands-on technical fluency with the ability to write and review data validation code.
