Senior Recommendation & Growth Machine Learning Engineer

Senior Recommendation & Growth Machine Learning Engineer Global / Relocation Available About the Opportunity We are building one of the most sophisticated personalization and recommendation ecosystems in the digital asset industry. The platform serves millions of users globally, processing large-scale real-time interactions across trading products, content, campaigns, communities, and user engagement journeys. As They continue to scale, They are investing heavily in next-generation recommendation systems that drive discovery, engagement, retention, and user growth. This is an opportunity to join a high-performing team working at the intersection of Machine Learning, Recommender Systems, Search & Ranking, User Growth, and Large-Scale Distributed Systems. You’ll tackle some of the most challenging recommendation problems in the industry, designing systems that operate in real time, influence millions of user decisions, and directly impact business growth What You'll Be Doing Design and develop large-scale recommendation and ranking systems powering personalized user experiences. Build low-latency real-time recommendation infrastructure across product discovery, content feeds, campaign targeting, user engagement, and community experiences. Develop advanced machine learning models including: Collaborative Filtering Deep Learning-based Recommenders Multi-Objective Ranking Systems Build and optimize end-to-end machine learning pipelines from feature engineering through deployment and monitoring. Design experimentation frameworks and conduct A/B testing to continuously improve recommendation quality and business outcomes. Work closely with Product, Data Science, Growth, and Engineering teams to identify opportunities for personalization and user engagement. Drive improvements in recommendation quality across metrics such as: CTRConversion Retention User Lifetime ValueSession Engagement Contribute to platform architecture and help define the long-term recommendation strategy. What We're Looking For Required Experience Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, or a related field. 5+ years of experience building and deploying production machine learning system's Strong hands-on experience developing recommendation, ranking, search, or personalization systems at scale. Deep understanding of machine learning fundamentals and modern recommendation algorithms. Experience with: TensorFlow PyTorch XGBoost LightGBMStrong programming skills in Python and SQL. Experience working with large-scale data processing frameworks such as Spark Flink Hadoop Familiarity with real-time serving architectures and low-latency ML systems. Experience measuring and optimizing business KPIs through experimentation and model iteration. Strong understanding of feature engineering, model evaluation, and production deployment practices. Experience building recommendationsystems for: Social Media E-commerce Marketplaces Digital Assets Knowledge of Graph Neural Networks (GNNs) and graph-based recommendation technique's Experience with reinforcement learning for recommendation and ranking problems. Exposure to Large Language Models and AI-driven personalization strategies. Familiarity with MLOps tooling, model monitoring, and large-scale ML infrastructure. Experience working with high-growth, global-scale products serving millions of users. Why Join? Solve complex recommendation and ranking challenges at massive scale. Build products used by millions of users globally. Work alongside elite engineers, researchers, and product leaders. Influence the future of AI-driven personalization within one of the fastest-growing sectors in technology. Own projects end-to-end with significant visibility and impact.Access significant opportunities for technical growth, leadership, and career #J-18808-Ljbffr Edison Smart®