Sr. Machine Learning Engineer, Apple Maps
Santa Clara Valley (Cupertino), California, United States
Software and Services
At Apple Maps, our mission is to build and maintain an accurate digital representation of the entire Globe. It is one of the most challenging large-scale problems in the world. We ingest a staggering amount of data and wish to discover new ways to use that data to improve the customer experience. Maps POI ML Engineering team builds platforms for data science teams that orchestrate data pipelines and run machine learning flows at scale to improve the quality of Points of Interest data in Apple Maps. In this role, you would enjoy working in a highly technical team, where everyone learns from each other's unique skills and knowledge. Your bias for action means you thrive in an environment where you can get things done. We encourage and respect critical thinking. Challenge yourself, challenge the data, challenge us.
- Excellent communication skills and ability to collaborate cross-functionally with data science and infrastructure teams.
- Hands-on in designing, building, scaling, and troubleshooting platform solutions to Big Data problems.
- Customer-focused mindset, with emphasis on user experience and productivity.
- ML engineering or data engineering background with more than 5 years of industry experience.
- Strong coding skills in Python, Scala, and/or Java.
- Experience with Kubernetes, Airflow, Spark, Hadoop, Cassandra, Kafka, AWS S3, and Elasticsearch/Solr/Lucene is a plus.
The successful candidate will join our POI Machine Learning Engineering team. We are responsible for developing frameworks and platforms for orchestration of data pipelines and ML flows. You will work cross-functionally with data science, infrastructure, and SRE teams to drive platform architecture in a way that facilitates prototyping, experimentation, and production deployment to ultimately allow data scientists to be more effective at implementing our key data strategies. You will collaborate with data scientists to design statistical and machine learning workflows on massive data and use acquired insights to propose and develop new platform capabilities that further improve data engineering efficiency.
Education & Experience
MS degree in computer science or related with 7+ years of experience or PhD with 4+ years