To build the freshest, most accurate maps, powering features that let users explore and navigate the world, by leveraging cutting-edge machine learning techniques to develop next-gen architecture focused on creating, updating and enriching business and places data while optimizing latency and cost.
Requirements
- 10+ years of experience in developing and deploying large scale, ML-centric systems and data pipelines on complex data domains in production settings
- 5+ years of hands-on-experience with using ML models in production systems to ship customer-facing features
- Strong foundational understanding of principles of distributed systems for large scale data processing
- Hands-on-experience with cloud platforms like AWS, GCP or Azure
- Deep mastery of developing & supervising production code in Scala, Java or C++ using ML toolkits like PyTorch, TensorFlow, Scikit-learn
- Familiarity with big data technologies like Spark, Solr/Lucene, Cassandra
Responsibilities
- Design, technology selection and implementation of systems built to handle relentless streams of change signals associated with our global Places database
- Drive the platform and architectural choices to enable complex, agentic workflows for multi-modal information extraction, geospatial processing and data updates
- Own design trade-offs between throughput, latency and cost of keeping Places data as accurate as possible
- Collaborate with world-class cross-functional teams, including engineers, data analysts, labelers, and validators, to develop innovative solutions
- Enable content and domain experts to experiment and iterate rapidly with data at scale without being exposed to the underlying compute complexity
- Provide technical guidance and mentorship to team members
Other
- Master's degree or equivalent experience in AI, Machine Learning, Mathematics, Computer Science, or a related field
- Strong interpersonal skills are essential for communicating technical complexities clearly to engineering partners, product management teams, and executives across Apple
