About the Team Launched in 2019, Constructor is an AI-first ecommerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains.
As a member of the Personalization team, you will improve the e-commerce experience for hundreds of millions of users across the world by designing, delivering & maintaining high-load real-time services in close collaboration with great engineers both within the team and across other teams such as the Ranking team.
The general goal of the Personalization team is providing best-in-class personalization for all e-commerce experiences provided by Constructor.
The job can consist of, but is not limited to:
Improve personalized experience across different products, domain verticals and platforms
Improve business KPIs by validating hypotheses around personalization
Research different personalization approaches to provide the best outcome to the business
Model user interactions to provide the best experience to shoppers
Collaborate with technical and non-technical business partners to develop and update personalization capabilities
Communicate with stakeholders within and outside the team
Requirements
Hard skills
3+ years of professional experience in applied machine learning
Proficiency with Python, SQL and the big data stack for end-to-end ML product development
Experience building, shipping, and maintaining personalization / recommender / ranking systems in production
Experience with any of the major public cloud platforms will be a plus
Experience with design and analysis of A/B tests
Great skills delivering & communicating business value to stakeholders
Soft skills
Excellent English communication skills
Experience collaborating in cross-functional teams
Ability to deep dive into problems and provide actionable outcomes
Ability to work autonomously and independently
Proactivity
Benefits
Work with smart and empathetic people who will help you grow and make a meaningful impact.
Regular team offsite events to connect and collaborate.
Fully remote team - choose where you live.
Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year.
Work from home stipend!
We want you to have the resources you need to set up your home office.
Apple laptops provided for new employees.
Training and development budget for every employee, refreshed each year.
Maternity & Paternity leave for qualified employees.
Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results
Stock options - offered in addition to the base salary.
Diversity, Equity, and Inclusion at Constructor
Constructor.io is committed to cultivating a work environment that is diverse, equitable, and inclusive.
As an equal opportunity employer, they welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group.
They encourage you to apply even if you don’t meet all of their listed qualifications.
How they handle your data
By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role.
If you are not selected, they will retain your data for a limited period as described in their Recruitment Privacy Notice.
After that period your data will be deleted or anonymized.
Responsibilities In this role, you’ll: Build out new functionality within a fast moving product seeing rapid adoption. Take a nebulous idea, design a rigorous experiment, and execute it within weeks.
Role Focus: Build and deploy production-grade AI/ML and Generative AI systems, with a focus on LLMs, RAG, personalization, MLOps, and cloud infrastructure. - Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants.
Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. Design and implement machine learning, deep learning, classical CV focused on fraud detection.
Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition). Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition). Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
-Define the long-term technical roadmap for Growth and Engagement ML systems, ensuring scalability, reliability, and measurable business impact. -Architect and deploy production-grade ML pipelines and real-time decisioning systems that power personalization, notification dispatch, and onboarding flows.
• Design and develop human-like, action-level chatbots that not only converse naturally but also initiate and execute user workflows inside the product. • Participate in the architecture and development of an intelligent, context-aware translation system that preserves meaning, tone, and style.
Задачи:
— Активное участие в найме, наставничестве и развитии карьеры других инженеров
— Повышение технических стандартов, производительности, надежности и операционного совершенства
— Определение областей, где машинное обучение может создавать ценность для клиентов
— Правильная постановка задач машинного обучения в продуктах, взаимодействие с командой и заинтересованными сторонами из Product и Design
— Проведение разведывательного анализа данных и исследований для глубокого понимания проблемной области
— Исследование и выбор подходящих алгоритмов и инструментов, сочетая прагматизм и инновации
— Проведение офлайн-оценки для подтверждения эффективности алгоритмов
— Сотрудничество с инженерами для вывода прототипов в продакшн
— Планирование, измерение и распространение результатов для информирования итераций
— Тесное взаимодействие с командой и другими подразделениями для создания отличных ML-продуктов
Требования:
— 5-8 лет опыта применения машинного обучения
— Предыдущий опыт на старшей или ведущей позиции (data science, разработка ПО или академическая сфера)
— Значительный и доказанный вклад в продукт и/или команды
— Сильные навыки программирования
— Опыт технического лидерства в команде
— Хорошие коммуникативные навыки внутри инженерных команд и между дисциплинами
— Умение работать в условиях неопределенности
— Обычно наличие продвинутого образования в области машинного обучения или смежной области (например, MSc)
— Научный подход к мышлению
Плюсы:
— Опыт выпуска ML-продуктов
— PhD или опыт работы в исследовательской среде
— Глубокие знания в применимых областях ML, таких как NLP, глубокое обучение, байесовские методы, обучение с подкреплением, кластеризация
— Сильный статистический или математический бэкграунд
— Навыки визуализации и работы с данными, включая SQL, matplotlib и др.
Условия:
— Гибридный формат работы с офисами в Дублине, Лондоне и Берлине
— Ожидается присутствие в офисе минимум три дня в неделю
— Компания предлагает конкурентные условия и поддержку баланса между работой и личной жизнью
— Политика равных возможностей и недискриминации
— Поддержка здоровья, благополучия, семьи, времени вне работы и финансового будущего
Компания:
Fin — крупная IT-компания, разрабатывающая интеллектуальных AI-агентов для автоматизации клиентского сервиса, теперь часть Salesforce. Их AI Agent Fin — один из лучших на рынке, обеспечивающий круглосуточную поддержку клиентов по всем каналам с минимальной настройкой и интеграцией. Команда активно применяет современные ML-технологии и тесно сотрудничает с продуктовой и дизайнерской командами для быстрого вывода продуктов на рынок.
Act as a learning consultant to our Disputes Experience line of business; gaining a deep understanding of the business and metrics to craft and recommend learning strategies to drive strong business outcomes.
What You'll Do: Design, build, and deploy machine learning models that predict key business outcomes such as churn, expansion, conversion, and customer engagement. Develop and maintain scalable ML pipelines that continuously ingest data, retrain models, validate performance, and serve predictions in production.
