Strategic Project Lead- MultiModal

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 Strategic Project Lead Multimodal AI Turing  |  Remote – LATAM  |  US Time Zone  |  Full-Time About the Role Turing is building the infrastructure layer for AI model development — delivering large-scale, production-grade data solutions across the most technically demanding AI programs in the world. As AI systems evolve beyond text into richer perceptual modalities — vision, image and video reasoning, generation, and audio — the need for specialists who can sit at the intersection of technical depth, delivery precision, and client trust has never been greater. The Multimodal AI SPL is a senior individual contributor and delivery leader who owns end-to-end program outcomes for clients at the frontier of multimodal model development. You will operate across vision, video, image generation, and audio workflows — building scalable annotation and evaluation pipelines, translating complex model requirements into executable production systems, and serving as the primary strategic partner for key accounts in the US market. This role is based in LATAM and aligned to US business hours. What You'll Do Client Partnership & Account Strategy Serve as the primary point of contact and strategic advisor for US-based clients across multimodal AI programs — owning the client relationship from scoping through delivery and expansion Translate complex, evolving model requirements across vision, video, image, and audio modalities into structured program plans with clear milestones, quality benchmarks, and risk posture Lead strategic conversations with client research and engineering teams, providing informed perspective on data quality trade-offs, modality-specific constraints, and delivery architecture choices Identify and develop account growth opportunities by understanding client roadmap priorities and proactively surfacing adjacent capability fits Program Architecture & Cross-Modal Delivery Design and own end-to-end delivery architecture for multimodal annotation, evaluation, and RLHF programs — spanning visual understanding, image/video generation quality, spatial reasoning, and audio-visual alignment Build scalable execution systems that account for the distinct complexity of each modality — frame-level video annotation, multi-step image generation evaluation, audio-visual consistency, and intermodal reasoning tasks Drive program governance including milestone tracking, escalation frameworks, and quality gates that span multiple concurrent workstreams Anticipate and resolve cross-functional dependencies across annotation, QC, tooling, and research teams before they become blockers Quality Systems & Model Alignment Own the quality architecture for multimodal programs — defining rubrics, calibration cycles, inter-annotator agreement protocols, and escalation logic tailored to modality-specific failure modes Partner with client ML and research teams to understand model evaluation criteria and ensure ground truth data aligns with downstream training and fine-tuning objectives Establish feedback loops between human evaluation signals and model performance metrics, enabling data-driven iteration on annotation schema and quality thresholds Maintain accountability for data quality outcomes at the program level, not just task level Talent & Team Capability Build and develop delivery teams with the right modality-specific expertise — sourcing, assessing, and onboarding annotators, QC reviewers, and leads who can operate across vision, video, and audio tasks Create structured onboarding and calibration programs that ramp team proficiency quickly on technically complex modality combinations Drive a performance culture oriented around quality ownership, cross-modal adaptability, and continuous improvement Operational Intelligence & Scalable Execution Develop and maintain program-level delivery intelligence — throughput metrics, quality trends, cost efficiency, and capacity utilization — that enables proactive decision-making and client reporting Build repeatable execution playbooks for multimodal program types that can be scaled a