Machine Learning Engineer, User & Content Intelligence

This is not a standard Data Engineering or ML role. We are looking for a pioneering engineer to join our team. You will build the systems that securely process, combine, and deliver the critical user and content features needed for personalization, spanning from edge devices to cloud backends. You will engineer high-performance stacks that transform raw data into governed, discoverable intelligence, ensuring that machine learning models can seamlessly and securely access the right user and content features regardless of where that data physically resides. Minimum Qualifications BS or MS in Computer Science, Data Engineering, Software Engineering, or a related field. Senior-Level Experience: A proven track record of shipping complex, large-scale data engineering, feature serving, or machine learning systems to production. Mastery of Big Data & Serving: Expertise in designing distributed data processing systems using technologies like Spark and Flink, and building low-latency, high-throughput data serving layers or Feature Stores. Strong Software Engineering: Deep proficiency in Java or Go for building high-performance production backend systems, and Python for model training ecosystems. Strategic Data Mindset: Demonstrated experience thinking critically about data architecture, including data ontology, discoverability, and bridging distributed data sources. Preferred Qualifications Hybrid/Edge Computing: Experience building systems that bridge cloud backend systems with on-device or edge compute environments. Embeddings & Vector Search: Familiarity with generating, managing, and serving dense embeddings for retrieval, ranking, and personalization systems. Data Governance: Experience building feature stores, data catalogs, or implementing compliance-by-design in a regulated environment. Privacy-Preserving Tech: Passion for privacy and an understanding of data minimization strategies, secure enclaves, or Privacy-Enhancing Technologies (PETs).