Client Director - Frontier Data

Turing • Palo Alto, CA

29d • $255,000 - $325,000 • Hybrid

About The Position

Based in San Francisco, California, Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage. Recognized by Forbes, The Information, and Fast Company among the world's top innovators, Turing's leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. We are seeking a seasoned techno-functional leader to drive the development and execution of large-scale LLM training programs. This role is deeply technical and client-facing with significant emphasis on dataset creation, annotation workflows, and high-quality data pipelines for foundational model training. The ideal candidate combines deep technical understanding of the LLM training lifecycle, strong operational rigor, and exceptional cross-functional leadership. This role will require someone who has had experience managing managers and performance-managing large distributed teams.

Requirements

• 10+ years of experience leading large-scale technical delivery organizations, ideally across AI, ML, or data operations.
• Proven success scaling and performance-managing teams of 100+, with distributed global operations.
• Experience managing managers
• Skip-level performance management
• Hands-on technical fluency: ability to write, read, and review Python scripts used for data validation, QA, and automation.
• Demonstrated experience managing dataset generation or annotation for LLMs (SFT, RLHF, or fine-tuning pipelines).
• Familiarity with ML tools and data workflows (e.g., HuggingFace, LangChain, Weights & Biases, Databricks).
• Strong understanding of data quality frameworks, including automation-based validation, inter-annotator consistency, and win-rate metrics.
• Bachelor's degree in Engineering, Computer Science, or equivalent technical discipline.

Nice To Haves

• Experience in AI Data Platform or ML infrastructure environments.
• Experience designing RAG, SFT, or RLHF pipelines and human-in-the-loop QA systems.
• Demonstrated ability to act as a strategic business partner while maintaining technical rigor.
• Strong communication and storytelling skills with executive stakeholders.

Responsibilities

• Operational Leadership & Performance Management Lead and scale global delivery teams of 100+, distributed across functions, regions, and levels (ICs, leads, and managers).
• Implement performance management systems that go beyond managerial reporting using data-driven metrics, tools, and products to assess productivity, quality, and output consistency.
• Build strong operational structures that allow for transparency, accountability, and early detection of underperformance.
• Partner with cross-functional leads to optimize workflows and improve internal tool adoption for delivery efficiency.
• Data Quality & Scripting-Driven Automation Own the quality, accuracy, and scalability of data generated for LLM training.
• Move beyond manual QA layers by leveraging Python scripting, APIs, and automation frameworks to measure, validate, and improve dataset integrity.
• Design and oversee tools or scripts for data validation, annotation accuracy checks, and pipeline consistency.
• Ensure datasets adhere to compliance standards (PII, GDPR, HIPAA) and can be programmatically tested for usability and quality.
• LLM Training & Evaluation Lead generation and delivery of high-quality, scalable datasets focused on SFT, RLHF, reasoning, and agentic workflows.
• Oversee the entire data lifecycle from client intake and annotation workflow design to delivery.
• Partner with product, research, and engineering teams to implement evaluation metrics (e.g., win rate, inter-annotator agreement, and pairwise preference scoring).
• Client Partnership & Communication Serve as the primary point of contact for enterprise AI clients; manage expectations, delivery timelines, and escalations.
• Build relationships with engineering and research stakeholders by delivering consistently high-quality data.
• Communicate effectively across technical and non-technical audiences; provide transparency through structured updates and quality reporting.
• Team Development & Tooling Recruit, mentor, and coach cross-functional leaders (Eng, Data, Ops, and Program Management).
• Drive adoption and improvement of internal tools (e.g., task management systems, quality dashboards).
• Champion continuous improvement across data quality, tools, and delivery processes.

Benefits

• Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
• Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
• Competitive compensation
• Flexible working hours

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Number of Employees: 1-10 employees