Requirements

Bachelor's degree in Computer Science or a related technical field; or equivalent professional experience
8+ years of relevant professional experience
Demonstrated ownership of machine learning solutions at the service or multi-service level, including problem definition, model development, evaluation, and operationalization
Strong foundation in machine learning methods, statistical analysis, experimentation, and data-driven decision making
Hands-on coding experience in scientific and production-oriented environments
Experience working with cross-functional partners to deploy technical solutions
Core expertise in scalable model development, data modelling, and integration into software systems

Nice to Haves

Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, Engineering, or related quantitative field
Experience delivering machine learning solutions at scale, including architecture, production monitoring, model lifecycle management, and operational excellence
Ability to influence technical direction through experimentation, scientific reasoning, and clear communication
Strong experience with recommendation, ranking, retrieval, search, personalization, ads, marketplace, or e-commerce applied ML systems
Experience with neural recommendation systems, sequential/session-based recommendation, transformer-based recommenders, semantic or generative retrieval, or representation learning at scale

Design, develop, and apply machine learning solutions to personalization, product, and business problems
Drive end-to-end scientific work including problem formulation, data exploration, feature engineering, model development, evaluation, and iteration
Partner closely with engineers, product, and business stakeholders to integrate ML solutions into services and workflows
Use strong technical judgment to select appropriate methods, validate outcomes, and improve model performance and reliability
Safely integrate and operate AI/ML-enabled solutions that improve outcomes
Stay informed about advancements in recommender systems and relevance algorithms through ongoing research
Contribute deep technical expertise and help raise scientific and engineering quality through experimentation, documentation, mentoring, and reusable approaches