Head of ML

Description JoomPro is the first end-to-end cross-border B2B marketplace. We aspire to create a new level of service in the wholesale purchasing market. We give everyone, anywhere in the world, the opportunity to order goods from factories in China easily and efficiently. After a successful launch in Brazil, we are now expanding to Mexico to bring seamless wholesale trade to new markets. JoomPro is one of the key businesses of Joom, an international tech-centric group of e-commerce companies founded in 2016 in Latvia. Joom Group also includes other businesses: Joom, a platform for global shopping; JoomPulse, a data platform that provides analytics and recommendations for marketplace sellers; and Onfy, a pharmaceutical marketplace in Germany. Joom Group has offices in Latvia, China, Portugal, Germany, and Brazil, with its headquarters in Lisbon, Portugal. We work as one international team, sharing knowledge and collaborating across countries, businesses and products. We are currently looking for the Head of ML to join the JoomPro team. You will be responsible for developing the following areas: Market intelligence (working with product content and assortment) Search (enhancing core search algorithms) AI assistants (improvement of existing ones and development of new ones) Logistics optimizations (optimization of logistics and warehouse operations using ML approaches) AI for engineering (implementing new AI approaches and tools in development) Tech stack: Go, Python, Scala, Spark, modern LLMs, PyTorch, Docker, Kubernetes, Airflow, MongoDB, Cassandra, Kafka, Jenkins. Our engineers are responsible not only for data analysis, hypothesis creation, modeling, and experimentation, but also for writing production code capable of handling high loads. Requirements Strong algorithmic skills: knowledge of fundamental algorithms and data structures, as well as their implementation in standard libraries Proficiency in any programming language: experience in developing and debugging distributed, high-load applications, and writing testable code Industry experience in Machine Learning: familiarity with key modeling and training approaches (linear models, GBDT, DNN, etc.), knowledge of statistics, and end-to-end ML development experience, including raw data analysis, hypothesis formulation, model creation, experimentation, and deploying results into production Experience in leading and developing the ML team by recruiting, hiring, and training new team members Experience in developing and implementing an ML department strategy Preferred Experience in developing recommendation or search systems Experience training neural network models Experience working with various data sources: Spark, Cassandra, Mongo, Kafka Knowledge of Go We offer Compensation package: base salary and performance-based bonuses Office-first: flexible hours with a possibility to work remotely 52 days per year Care & Wellbeing: health insurance (including dental care) for employees and their children, daily meal allowance, and 100% paid sick leave Relocation Support: full assistance for a smooth relocation for the employees and their family Team & Growth: collaboration with colleagues across Portugal, Brazil, Latvia and China, with opportunities for promotions, professional trainings, and English & Portuguese courses Community & Engagement: annual team building activities, knowledge-sharing workshops, and a strong sense of team work Before applying for the above position please review our Candidate Privacy Notice here. By responding to the vacancy, you acknowledge that you have read our Privacy notice. Requirements Strong algorithmic skills: knowledge of fundamental algorithms and data structures, as well as their implementation in standard libraries Proficiency in any programming language: experience in developing and debugging distributed, high-load applications, and writing testable code Industry experience in Machine Learning: familiarity with key modeling and training approaches (linear models, GBDT, DNN, etc.), knowledge of statistics, and end-to-end ML development experience, including raw data analysis, hypothesis formulation, model creation, experimentation, and deploying results into production Experience in leading and developing the ML team by recruiting, hiring, and training new team members Experience in developing and implementing an ML department strategy