Staff Machine Learning Engineer, Platform

Samsung Electronics is a fast-growing advanced advertising technology company that empowers advertisers to connect with audiences across Samsung devices through digital media. The role of Staff Machine Learning Engineer on the Platform Intelligence team involves developing and maintaining machine learning platform components to support large-scale model training and batch prediction systems, while collaborating with internal teams to enhance the platform's reliability and efficiency. Responsibilities: Develop and maintain machine learning platform components that support large-scale model training pipelines and batch prediction systems; Contribute to building a world-class ML platform tailored for Samsung's ML-based advertising business; Build and improve CI/CD pipelines, data workflows, and monitoring systems to enhance platform reliability and efficiency; Assist in researching and evaluating new machine learning platform technologies through prototypes and proof-of-concepts; Collaborate with internal ML teams (e.g., ML Serving and ML Engineering) to improve codebase quality and product health; Work with cross-functional partner teams to support the delivery of new ML features and solutions; Troubleshoot issues, optimize system performance, and contribute to engineering best practices; Learn quickly and adapt to a fast-paced working environment Qualifications: 3-4 years of industry experience with a Bachelor's degree, or 2 years of industry experience with a Master's degree in Computer Science or related fields such as Statistics, Data Science, Technology, Engineering, or Mathematics; Solid programming skills in Python, with familiarity in SQL and databases; Foundational knowledge of machine learning concepts and hands-on experience with at least one ML framework (e.g., TensorFlow, PyTorch, or Spark ML); Familiarity with big data tools and concepts (e.g., Spark, Kafka, or similar technologies); Basic understanding of containerization (Docker) and orchestration (Kubernetes); Exposure to CI/CD pipelines, version control (Git), and software engineering principles; Understanding of data structures and algorithms; Good communication skills and ability to collaborate effectively in a team environment; Eagerness to learn new technologies and adapt to a fast-paced environment Required Skills: Python, SQL, Machine Learning, TensorFlow, PyTorch, Spark ML, Big Data Tools, Spark, Kafka, Docker, Kubernetes, CI/CD Pipelines, Git, Data Structures, Algorithms