The Maps Places Data team at Apple needs to improve and maintain the quality of all Places of Interest in the global maps database by developing next-generation algorithms and processes.
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
- Produce algorithms and processes that can operate globally, leveraging all available signals from aerial imagery to users’ feedback.
- Create the next generation of algorithms and processes to solve challenging problems in the mapping domain.
- Build large scale machine learning systems.
- Develop and implement machine learning models.
- Leverage spatiotemporal signals to improve and maintain the quality of Places of Interest.
- Design algorithms in the mapping domain.
- Apply classical computer vision techniques and modern solutions based on foundation models.
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.
