Head of Production, Applied AI
LILT
full-time
Posted on:
Location Type: Hybrid
Location: New York City • District of Columbia • Massachusetts • United States
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Job Level
About the role
- Define and execute the vision and strategy for Applied AI production operations
- Lead end-to-end production operations for Applied AI, ensuring on-time, high-quality delivery
- Build, mentor, and scale a high-performing production team, including project managers, data specialists, and quality assurance professionals
- Design and implement standardized processes, workflows, and quality frameworks across production teams
- Optimize resource allocation, prioritization, and capacity planning to maximize team productivity
- Establish metrics and KPIs to measure operational efficiency, quality, and business impact
- Communicate value, progress, and strategic initiatives effectively to executive stakeholders
- Drive continuous improvement initiatives and identify opportunities for innovation
Requirements
- 10+ years of experience in ML Data production operations, program management, or related roles
- 5+ years leading complex ML/AI Data delivery programs at scale
- Proven track record of scaling operations from small teams (5-10) to enterprise-level (50+)
- Experience managing multi-million dollar budgets and P&L responsibility
- Deep understanding of AI/ML workflows, training data requirements, and quality standards
- Expertise in data annotation, labelling, model benchmarking and evaluation, and data pipeline operations
- Knowledge of data science, engineering principles, and linguistics as they apply to AI production
- Experience with production tooling, platforms, and technologies for Applied AI operations
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ML Data production operationsprogram managementAI/ML workflowsdata annotationdata labelingmodel benchmarkingdata pipeline operationsquality standardsdata scienceengineering principles
Soft Skills
leadershipmentoringcommunicationstrategic thinkingresource allocationprioritizationcapacity planningcontinuous improvementteam productivitystakeholder engagement