At The Knot Worldwide, we champion celebration - and that starts with celebrating our people. Our employees are passionate dreamers, thoughtful doers, and lifelong learners who power meaningful moments for millions around the world. We’re united by authentic connection, shared purpose, and a deep commitment to the global community we serve. Here, flexibility and belonging go hand in hand with high performance. We believe the best ideas come from empowered teams: those who consistently collaborate with intention to design solutions, spark ideas, and drive impact. We inspire, we build, and we celebrate. We dream big, love our users, hustle every day, and always do the right thing to win - together. Our people are at the heart of our success.
ABOUT THE ROLE AND THE TEAM:
The Machine Learning team at The Knot Worldwide builds the intelligence that powers search, recommendations, personalization, and AI-assisted experiences across our global wedding marketplace. We’re a fast-moving, collaborative, and highly technical team that partners deeply with product, engineering, and design to deliver ML-powered features that drive real user and business impact.
The strategic and technically rigorous Lead Machine Learning Scientist (you!) will help define the future of our AI capabilities and build models that connect couples to the right vendors, content, and products at the right time. You will lead the design, development, and deployment of machine learning solutions across ranking, recommendations, semantic search, and generative AI, driving measurable improvements in conversion, engagement, and marketplace value. You will work closely alongside engineering, product, and data partners, and report to the Director of Machine Learning.
RESPONSIBILITIES:
- Lead the development of production-grade ML models across personalization, search ranking, NLP, and computer vision to power key user and vendor experiences.
- Collaborate with engineering and product to scope and ship end-to-end solutions that are scalable, reliable, and impactful.
- Mentor and guide a team of ML scientists, promoting best practices in experimentation, model architecture, and code quality.
- Drive adoption of MLOps principles for model deployment, versioning, observability, and monitoring.
- Partner with stakeholders to identify high-impact ML opportunities aligned with business goals, and clearly communicate trade-offs and results.
- Stay current on advancements in AI and apply new techniques to enhance the performance and efficiency of our models.
SUCCESSFUL CANDIDATES HAVE:
- 7+ years of hands-on experience in data science or ML roles, including at least 2 years in a technical leadership capacity.
- Advanced degree (PhD or Master’s) in Computer Science, Machine Learning, or a related technical field.
- Expertise in ranking, recommendation systems, deep learning, NLP, or computer vision, ideally in a consumer tech or marketplace context.
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
- Experience building and deploying models to production using MLOps tools and cloud-based infrastructure.
- Strong communication skills and ability to drive projects across cross-functional teams.
BENEFITS:
- Private health insurance
- Life insurance
- Employee assistance program: on-demand mental health assistance program for any professional or personal matter
- Optional salary advances
- Tax relief options: pre-tax savings for food, transport, daycare and work related training expenses
- Gym membership discount
- Udemy courses
- Personal time off: 23 working days of holidays per year + additional days each year considering the application of the max. anual working hours of the Collective Bargaining Agreement
- Other leave entitlements: nhancements to statutory leave permissions, for instance: maternity, paternity, childcare, illness and others to support work-life balance
- Work from home allowance (40€/month)
- Food allowance (55€/month)
- Employee gifting
- Signature events
- Employee resource groups
- DEI & Sustainability councils
- Robust communication and feedback channels
- Focused Fridays
- Recognition iniciatives
- Local events
- GROW program
- TKWW University for Employee & Leader development
- Employee referral program
WORK MODEL:
This role is Together@TKWW-eligible and based near one of our office hubs. Starting September 15, 2025, you’ll be expected to work in the office two days a week as part of our hybrid work model.
At The Knot Worldwide, we believe you are more than a resume and invite you to go for it, take the leap of faith, and apply for this job if it sparks your passion to join TKWW and make a difference!
WHAT WE LOVE ABOUT YOU:
You Dream Big. You iterate and experiment to drive innovation.
You Love Our Users. You keep our global community at the center of everything you do.
You Do the Right Thing. You strengthen your team through respect, fairness, and inclusion.
You Hustle Every Day. You favor urgency and own your outcomes.
You Win Together. People are at the heart of our success and you play as a team.
WHAT YOU LOVE ABOUT US:
We believe in a wide range of holistic offerings to support our employees so that they can live our values day in and day out. From mental wellbeing, physical health and financial planning, to engaging perks and discounts, we are in the business of celebrating and supporting the Moments that Matter both in and out of the “office”. We offer flexible vacation, generous parental leave and prioritize initiatives that support the growth, development, and happiness of our people.
Together@TKWW is our approach to hybrid work. It’s designed to support how we work best: combining the flexibility we value with meaningful opportunities to connect in person. Whether a role is Together@TKWW-eligible or not, we believe in purposeful moments to come together, build strong relationships, and drive bold ideas forward.
- For Together@TKWW-eligible roles, this includes regular in-office time to foster collaboration and connection.
- For roles not eligible for in-office expectations, we support connection through virtual collaboration and intentional gatherings.
