As Director of AI, you will lead and expand a group of algorithm engineers embedded in Product pods, play a pivotal role in roadmap planning, and balance cutting-edge research with practical productization. You will drive cross-organizational initiatives that elevate our products and operations, defend our competitive moat, and unlock new opportunities for growth and innovation.
Key Responsibilities
Team & Talent Leadership
Manage, mentor, and inspire a team of algorithm engineers, fostering technical excellence and career growth.
Scale the AI team through hiring, skill development, and cultivating a strong data science culture.
Promote cross-functional collaboration, execution, knowledge sharing, and experimentation.
Attract senior AI talent to build strong teams.
AI Roadmap & Innovation
Execute the AI roadmap, aligned with the company strategy and product vision.
Introduce state-of-the-art techniques to solve complex challenges.
Drive initiatives that push the boundaries of whats possible, turning AI into a measurable business differentiator.
Technical Leadership
Personally led the resolution of the most complex AI/ML challenges.
Architect and guide the implementation of production-ready ML systems, ensuring robustness, accuracy, and low latency.
Maintain a strong applied research perspective while delivering practical, business-impacting solutions.
Defending & Expanding Our Moat
Keep us ahead of industry shifts by monitoring emerging technologies and evaluating competitive threats.
Build defensible AI assets – unique data pipelines, proprietary models, domain-specific enhancements – that are hard to replicate.
Shape intellectual property (publications, patents, methodologies) that strengthens our positioning.
10+ years of professional experience in AI/ML and data science with at least 5 years in leadership roles.
Advanced degree (MSc/PhD) in Computer Science, Mathematics, or related field.
Proven success leading data science / AI teams in production environments.
Strong grounding in ML/DL, model architectures, and data pipelines.
Track record of translating research into scalable production systems with measurable business impact.
Practical trade-off mindset – build vs. buy, open-source vs. proprietary, etc.
Excellent communication skills – capable of influencing executives, mentoring engineers, and educating non-technical stakeholders.
Passion for continuous learning, innovation, and knowledge sharing.
