Director of Machine Learning & Artificial Intelligence

Responsibilities

• Shape and lead Thorn’s Machine Learning and AI strategy in partnership with Build leadership, Product, and cross-functional stakeholders, evolving technical direction as emerging technologies, research, customer needs, and the child safety landscape change
• Identify promising ML and AI technologies and approaches, translating research and experimentation into recommendations about where Thorn should invest, partner, build, or evolve its product and technology strategies
• Support Thorn’s Technical Innovation Roadmap through the exploration, prototyping, de-risking, and validation of new technical capabilities to advance mission impact and inform future product strategy
• Ensure ML systems and practices meet Thorn’s expectations for privacy, security, responsible AI, regulatory compliance, reliability, and operational excellence, including appropriate oversight of sensitive datasets, external data annotation partners, and CSAM reporting processes
• Partner closely with the Business Development and Strategic Impact (BDSI) team to inform Thorn’s technical research roadmap and enable exploration by connecting research questions, ML expertise, emerging opportunities, and product needs
• Build on the strengths of an established, highly skilled Machine Learning team while developing the people, leadership, and capabilities Thorn will need next
• Recruit, develop, empower, and retain exceptional ML talent, maintaining a high bar for technical excellence, collaboration, curiosity, and mission alignment
• Lead, coach, and develop technical leaders and individual contributors of various levels, creating clear ownership and meaningful opportunities for people to grow their skills and their impact
• Earn trust through curiosity, consistency, transparency, active listening, and strong follow-through
• Thoughtfully evolve team culture and ways of working as Thorn’s needs change, preserving the strengths already present while strengthening collaboration, adaptability, and shared ownership
• Foster psychological safety alongside high expectations, healthy disagreement, technical excellence, continuous learning, and accountability
• Set clear expectations and provide timely, candid feedback. Recognize strong performance and address performance concerns thoughtfully and directly
• Build leadership capacity throughout the team, delegating ownership and decision-making to the appropriate leaders and experts
• Partner with People & Culture on hiring, onboarding, development, performance management, and succession planning, in ways that strengthen team cohesion, uphold our values, and support a culture of excellence and care
• Build deep partnerships across Machine Learning, Engineering, Product, BDSI, and other teams, strengthening collaboration across the SDLC so research, experimentation, product development, and production delivery remain connected throughout the lifecycle
• Partner closely with Engineering leadership and teams to ensure ML capabilities are designed, built, deployed, and operated as reliable, scalable, production-ready systems, with shared technical context and clear ownership
• Partner with Build leadership and Technical Program Management to align ML priorities, dependencies, investments, and capacity with Build’s broader strategy and roadmap
• Help shape cross-Build technical decisions by bringing ML expertise and perspective, while strengthening collaboration across disciplines and empowering the appropriate teams and technical leaders to own decisions within their areas
• Partner with Product, Engineering, BDSI, and customer-facing teams to ensure customer and ecosystem learning informs ML priorities and continuous improvement
• Partner across Build to strengthen shared approaches to responsible data use, privacy, security, and ML governance
• Establish clear priorities, expectations, and operating rhythms that help the ML team deliver predictably while maintaining space for innovation and learning
• Ensure sustainable ML development and operational practices that appropriately balance speed, quality, reliability, cost, security, and long-term maintainability
• Empower technical leaders and senior individual contributors to own day-to-day execution while maintaining visibility into progress, risks, dependencies, and organizational needs
• Partner with Finance and Build leadership on responsible resource allocation, headcount planning, infrastructure investment, and budget stewardship
• Identify organizational or technical constraints early, make clear tradeoffs, and help teams align and move forward when priorities or perspectives compete
• Serve as a member of Build’s leadership team, contributing to Build strategy, organizational planning, emerging threat response, investment decisions, and complex problem-solving
• Represent Thorn’s ML work externally with customers, strategic partners, funders, conferences, advisory groups, and the broader technical community as appropriate

Benefits

• Remote-first work model structured around working from home most of the time; employees are expected to travel at times for company-wide gatherings, in-person team meetings and team-building events, or specific conferences.
• Glassdoor
• 4.6
• Technology tools protecting children from online sexual exploitation.
• El Segundo, California, USA
• https://www.thorn.org/
• Growth Stage
• Total Funding
• $0.34M
• Key Investors
• Patrick J. McGovern Foundation
• Sahsen Ventures
• 2023-12-20
• Grant· $0.34M
• 2017-01-01
• Grant
• Leadership Team
• Julie Cordua
• CEO
• Recent News
• PR Newswire
• Safer by Thorn Launches Context Labels to Help Platforms Prioritize Most Severe Suspected CSAM Faster
• 2026-07-14
• Newsfile
• Compassion International and The Thorn Celebrate Milestone: 25,000 Children Sponsored
• 2026-04-08
• THE AUDACIOUS PROJECT NAMES NEW GRANTEE COHORT CATALYZING GLOBAL CHANGE
• 2026-02-25
• Company data provided by
• AI Tools

Qualifications

• Significant experience leading ML, AI, Data Science, or related technical teams responsible for production capabilities at meaningful scale
• Strong technical judgment across modern ML and AI, with the ability to guide direction, evaluate tradeoffs, and translate emerging technologies and research into practical capabilities and strategic direction
• Deep understanding of AI/ML applications, content detection technologies, and software development
• Experience developing and operating ML capabilities with appropriate attention to reliability, evaluation, monitoring, privacy, security, and responsible AI
• Proven ability to lead, develop, and strengthen high-performing technical teams, including attracting, hiring, and retaining exceptional talent
• Experience coaching technical leaders and individual contributors, delegating ownership appropriately, setting clear expectations, and providing candid, constructive feedback
• Ability to earn trust with an established team and thoughtfully evolve culture while fostering psychological safety, accountability, inclusion, and high expectations
• Track record of strong collaboration with Engineering, Product, Research/BDSI, and other cross-functional partners, including moving capabilities from research and experimentation into reliable production systems
• Skilled at navigating complex stakeholder environments, creating alignment across teams, and providing direction and coaching where needed
• Ability to influence, drive change, and solve complex problems calmly and strategically
• Strong communication skills, including asking critical questions, communicating key points clearly, and representing technical work externally through partner conversations, conferences, fundraising events, or advisory forums
• Lead with empathy, humility, honesty, clarity, and a trauma-informed approach
• Build relationships based on trust, transparency, accountability, and follow-through
• You have a commitment to putting the children we serve at the center of everything you do

Required skills

• Artificial Intelligence, Content Detection, Data Science, ML Evaluation and Monitoring, Machine Learning, Privacy and Security, Production ML Systems, Responsible AI, Software Development