Client Director, Frontier Data - US
Turing Palo Alto, California, United States; San Francisco, California, United StatesUSD 255,000–325,000 / yearLead
Key requirements
- Python
- Go
- Machine Learning
- Llm
- Agile
- Compliance
About Turing
Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com .
Overview
We are seeking a seasoned techno-functional leader to drive the development and execution of large-scale LLM training programs. This leader would partner with our clients (leading LLM labs) research teams to:
Identify opportunities for building training datasets to improve model capabilities and performance
Generate these datasets with high quality and speed
Build automation tools and processes for scalability
Deliver the datasets so that they are easily usable by our clients
Key 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
Required Qualifications
10+ years of experience leading large-scale technical delivery organizations, ideally across AI, ML, or data operations
Bachelor's degree in Engineering, Computer Science, or equivalent technical discipline
Demonstrated ability
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