Lead Generative AI Analyst - English (US)

Official role information

We're looking for an experienced Lead Generative AI Analyst to join our team. This leadership role is open to hybrid and remote candidates, with a preference for those who can work in a hybrid capacity from our Santa Clara, CA office. We're looking for someone who enjoys leading AI operations, coordinating people, solving complex operational challenges, and building scalable processes in a fast-paced Generative AI environment. Rather than focusing on individual annotation work, you'll lead the end-to-end execution of AI data initiatives, partnering with annotators, quality teams, AI researchers, engineers, and cross-functional stakeholders to deliver high-quality results efficiently and consistently. #LI-CC1 What You'll Do - Lead the day-to-day operations of teams of multimodal AI annotators and reviewers. - Provide people leadership, including coaching, performance management, workload planning, and team development. - Own project execution across multiple workstreams, balancing quality, timelines, and operational priorities. - Own client-facing meetings, providing project updates, discussing risks, action plans, and delivery progress. - Translate business and technical requirements into clear, scalable operational workflows. - Build and improve processes, including zero-to-one workflows where requirements are not yet fully defined. - Identify and resolve operational bottlenecks, risks, and escalations to keep projects on track. - Partner with AI Research, Engineering, Product, Quality, and Operations teams to improve workflows and resolve complex issues. - Monitor quality, productivity, throughput, and project health, using data to drive continuous improvement. - Develop and refine annotation guidelines, documentation, and quality standards. - Coordinate calibration sessions and quality reviews to ensure consistent decision-making. - Support onboarding, coaching, and development of team members. - Prepare regular reports on project status, quality trends, and key operational metrics. What We're Looking For - 5+ years of experience in AI data operations, data annotation, content quality, Trust & Safety, data labeling, or similar production environments. - 3+ years of experience leading teams and managing projects, with ownership of delivery, quality, and operational outcomes. - Experience managing multiple priorities and workstreams in a fast-paced, high-ambiguity environment. - Experience building or improving operational processes and workflows. - Experience leading client meetings and communicating with internal and external stakeholders. - Strong stakeholder management, communication, and problem-solving skills. - Good understanding of AI data workflows and modern machine learning concepts, including data curation, human-in-the-loop workflows, RLHF, or fine-tuning. - Excellent written and verbal English. - Exceptional organizational skills and the ability to adapt quickly to changing priorities. - Experience creating documentation, operational processes, or quality guidelines. - Comfortable making decisions in ambiguous situations while maintaining consistency and accuracy. Preferred Qualifications - Experience leading Generative AI, machine learning, LLM, or multimodal annotation programs. - Experience working with AI researchers, engineers, Product, or technical teams. - Experience with QA operations, calibration, audits, or quality improvement initiatives. - Familiarity with annotation tools and AI data workflows. - Experience with workflow optimization, dashboards, or process improvement. - Basic Python, SQL, or data analysis skills are a plus.

Review the linked official posting for the complete current wording, application questions and any location-specific terms.

• Experience leading Generative AI, machine learning, LLM, or multimodal annotation programs. - Experience working with AI researchers, engineers, Product, or technical teams. - Experience with QA operations, calibration, audits, or quality improvement initiatives. - Familiarity with annotation tools and AI data workflows. - Experience with workflow optimization, dashboards, or process improvement. - Basic Python, SQL, or data analysis skills are a plus.

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