Director of Machine Learning & Artificial Intelligence
thorn
1 month ago
Full-time
On-site
Remote (US-Based), some travel required
$188,000 - $302,450 USD yearly
AI
Moneyboard classification: Published range reaches threshold
Reported USD annual base: $188,000–$302,450
Original source: Greenhouse
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 Organizatio
Reported USD annual base: $188,000–$302,450
Original source: Greenhouse
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 Organizatio