Technical Program Manager - Turing

About Turing

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. Learn more at www.turing.com

Job Description: Technical Program Manager – AI/LLM Training Programs

Role Overview

We are seeking an experienced Technical Program Manager (TPM) to oversee end-to-end program management for AI/LLM training initiatives, large-scale dataset creation efforts, and cross-functional operations with our global data partners. This role requires a strong technical foundation, exceptional stakeholder management skills, and an ability to drive complex, multi-team programs to success.

You will work closely with data scientists, ML engineers, annotation teams, QA specialists, and external partners to ensure projects are delivered with consistent quality, on time, and within scope.

Key Responsibilities

Program Planning & Execution

• Lead strategic planning, execution, and delivery of AI/LLM training programs and dataset creation projects.
• Define program scope, milestones, KPIs, and timelines; manage risks, resource needs, and dependencies.
• Build and maintain program dashboards, progress reports, and documentation for internal and external partners.

Cross-Functional Coordination

• Collaborate with data labs, engineering, research, annotation, QA, and vendor teams to align goals and drive execution.
• Manage communication across technical and non-technical stakeholders, ensuring clarity and accountability.
• Facilitate sprint planning, standups, and operational reviews for multi-stream program teams.

Quality & Process Management

• Implement scalable processes for data quality oversight, annotation workflows, and model training pipelines.
• Monitor dataset quality metrics and coordinate issue resolution with labeling and QA teams.
• Drive continuous improvement initiatives across tools, workflows, compliance, and documentation.

Technical Leadership

• Understand data schemas, ML model training needs, labeling guidelines, and evaluation frameworks.
• Work wi