Job description

At Thorn, our cause is our code. We are a nonprofit whose mission of defending children from sexual exploitation and abuse is deeply embedded within our core—a shared code that drives us to do challenging work with resilience and determination. Here, you’ll work and grow among the best hearts and the best minds in tech, data, and business alongside our network of independent partners, NGOs, and law enforcement agencies. Together, we’re focused on building technology that protects children’s futures. We are looking for dynamic problem solvers with the desire to help address some of today’s toughest issues. You'll collaborate with a diverse group of peers in a remote environment centered on wellness, care, and compassion. In 2019, we took the stage at TED and shared our audacious goal of eliminating child sexual abuse material from the internet. Come join us to help make this goal a reality and build a world where every child can be safe, curious, and happy. About the Role As Thorn’s Director of Machine Learning & AI, you will lead and build the team responsible for applying machine learning and AI to some of the most difficult technical challenges in our mission. You will shape and lead the strategy for the function, develop its people and technical leaders, and ensure ML expertise is deeply integrated into Thorn’s products, technical innovation, and broader Build strategy. You will lead an established core of passionate ML engineers with deep technical and mission expertise, while also having the opportunity to grow the team and shape the capabilities Thorn will need next. This role requires an exceptional people leader who can earn trust, build on the strengths already present, recruit outstanding new talent, and help the team evolve as Thorn’s needs and technical opportunities change. As a member of Build leadership, you will report to the CTO and partner closely with Engineering, Product, and other teams across the organization to align ML priorities and technical direction with Thorn’s broader strategy. What You’ll Do Technical Strategy and Innovation 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. Develop an Exceptional ML Team 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. One Build Collaboration 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. Execution and Organizational Leadership 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. What We’re Looking For Technical Strategy and Execution 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. Team Culture and Cross-functional Collaboration 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. Leadership 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. Compensation and Benefits A reasonable estimate of the compensation range for this role is $188,000 - $302,450/year . This range takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to location; skill sets; experience and training; licensure, and certifications. Our remote-first work model is structured around working from home most of the time. But, there will be times that employees are expected to travel. For example, Thorn may host company-wide gatherings, and smaller teams may hold in-person meetings and team-building events, or require attendance at specific conferences. At Thorn, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Thorn can mean for you . Thorn is strengthened by the wide range of experiences and perspectives on our team. We value the diversity of our professional backgrounds, subject matter expertise, cultures, and perspectives because they help us solve complex problems and serve our mission more effectively. We hire based on merit, qualifications, and organizational need, and we are committed to fostering an inclusive environment where all employees can thrive. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Thorn is committed to the full inclusion of all qualified individuals. We provide reasonable accommodations to ensure candidates and employees with disabilities can fully participate in the application process, perform essential job functions, and access all the benefits and privileges of employment. If you need an accommodation, please contact us at hiring@wearethorn.org Know Your Rights: Workplace discrimination is illegal

Requirements

Must-haves

What You’ll Do
Technical Strategy and Innovation
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.
Develop an Exceptional ML Team
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.
One Build Collaboration
Partner with Build leadership and Technical Program Management to align ML priorities, dependencies, investments, and capacity with Build’s broader strategy and roadmap.
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.
Execution and Organizational Leadership
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaiml

Platform: greenhouse
Effort: quick

Benefits

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Wellness