Director, AI

About the Director, AI at Headspace:

At Headspace, you’ll have the unique opportunity to shape the future of AI in mental healthcare, driving innovative, impactful solutions that touch the lives of millions around the globe. Our mission is to improve the health and happiness of people worldwide, and your leadership will be central to advancing cutting-edge AI-driven technologies that transform how individuals access and experience mental health support.

As the Director of AI, you will lead groundbreaking initiatives across diverse and dynamic business areas, from enhancing user engagement to delivering highly personalized care at scale. You’ll oversee the research, design, implementation, and optimization of advanced, responsible AI systems that are not only scalable and secure but also set the standard for innovation in the health tech industry. Your work will focus on ensuring our products remain at the forefront of technology, delivering measurable impact and aligning with our mission to transform mental healthcare.

In this role, you will collaborate closely with cross-functional teams, inspiring and empowering them to integrate AI seamlessly into our products to create transformative, data-driven experiences for our users. Whether it’s leveraging the latest machine learning models or exploring emerging AI trends, your vision and expertise will fuel the development of solutions that redefine how mental health services are delivered.

Join us on this exciting journey to revolutionize mental healthcare with AI and leave a lasting, global impact on health and well-being.

What you will do:

• Drive AI Vision & Strategy: Define and execute a strategic roadmap for AI/ML solutions while staying at the forefront of cutting-edge AI practices and developing publishable innovations.
• Build Scalable AI Infrastructure: Develop and maintain a high-performance, user-centric ML platform enabling scalable and flexible AI adoption across the organization.
• Ensure Responsible, Ethical AI: Develop and maintain robust safety and quality controls for AI use in a metal health domain, inclusive of both fully automated and human-in-the-loop mechanisms.
• Lead Cross-Functional Collaboration: Partner with clinicians, statisticians, and other experts to measure and enhance the impact of AI-driven solutions for mental healthcare.
• Ensure Operational Excellence: Optimize training data pipelines and feedback loops, ensuring our AI systems are scalable, secure, and robust, adhering to software development best practices.
• Promote Data-Driven Culture: Foster experimentation and measurement, empowering teams to integrate closely monitored AI/ML capabilities effectively and with confidence.
• Collaborate on Integration: Work closely with other tech teams to align AI infrastructure and operations with broader company systems and infrastructure.

What you will bring:

Required Skills:

• Proven Leadership: 10+ years of experience building, leading, and managing high-performing, innovative AI, machine learning, and/or data science teams, with a history of successfully delivering impactful, responsible AI-driven solutions at scale.
• Technical Expertise: Deep understanding of machine learning frameworks (e.g., TensorFlow, PyTorch), AI methodologies, and modern engineering tools, with hands-on experience deploying solutions in cloud environments (preferably AWS). A track record of publishing successful AI innovations is highly desirable.
• Preferred Domain Expertise: Experience working in consumer-facing health tech, mental health, or clinical settings, with a strong understanding of the challenges and opportunities in applying empathetic and responsible AI in healthcare, is highly desirable.
• Advanced AI Knowledge: Expertise in implementing multiple AI approaches at scale, including LLMs (productionizing LLM-driven solutions), recommendation systems, reinforcement learning, or advanced optimization techniques.
• Platform Development: Demonstrated ability to design, build, and scale machine learning platforms, architect robust data pipelines, and manage infrastructure and operations to support AI/ML production environments efficiently.
• Scalability & Performance: Experience designing evaluation systems, tests, and feedback loops to ensure AI/ML systems meet scalability, reliability, and performance standards while adhering to modern software development and engineering best practices.
• Business Strategy Alignmen