Improving and maintaining the quality of all Places of Interest in the global maps database at Apple
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 challenging problems
- Produce algorithms and processes that can operate globally, leveraging all available signals from aerial imagery to users’ feedback
- Deliver complex ML-powered features
- Operate on large scale machine learning systems
- Leverage spatiotemporal signals to improve the quality of Places of Interest
- Maintain the accuracy of a variety of attributes for the Points of Interest in the map database
- Collaborate with cross-functional teams to deliver high quality results
Other
- Strong problem-solving, communication, and ability to collaborate with cross-functional teams
- Solid track record of delivering complex ML-powered features
- Metrics focused and passionate about delivering models that render high quality results
- 7+ years of experience
- Ability to work at Apple
