The Maps Places Data team at Apple is looking to improve and maintain the quality of all Places of Interest in the global maps database by developing the next generation of algorithms and processes to solve challenging problems related to the accuracy of various attributes for Points of Interest.
Requirements
- 7+ years of experience in building large scale machine learning systems.
- Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Scala, Python, Java, or C++
- Knowledge of Spark, Solr/Lucene, Cassandra, and related big data technologies
- Familiarity with cloud platforms such as AWS, GCP, or Azure.
- Strong spatial aptitude and intuition for algorithm design in the mapping domain
- Experience with classical computer vision techniques and modern solutions based on foundation models
Responsibilities
- create the next generation of algorithms and processes to solve these challenging problems
- produce algorithms and processes that can operate globally, leveraging all available signals from aerial imagery to users’ feedback
- building large scale machine learning systems
- delivering models that render high quality results
- delivering complex ML-powered features
Other
- Metrics focused and passionate about delivering models that render high quality results
- Strong problem-solving, communication, and ability to collaborate with cross-functional teams.
- Solid track record of delivering complex ML-powered features.
