ML Engineer - Maps Navigation

Apple
Cupertino, United States of America2026-03-09

About the job

Helping people travel safely is one of our primary functions here on Apple Maps. We are the traffic team at Apple Maps and our main mission is to deliver accurate travel times and incidents for the world in realtime. We want to make sure that our recommendations are as accurate and responsive to external factors as possible, and we are looking for a machine learning engineer to help us provide the most accurate and reliable navigation experience possible!

Responsibilities

Designing, implementing, and maintaining algorithms and ML models for traffic prediction to support navigation decisions

Creating new technical capabilities that serve as building blocks for new and improved features that surprise and delight our customers

Working across multiple engineering, data science, UX, and product teams to help set the future direction of the product

Collaborating with data engineers to process and analyze extensive streams of location data in privacy-preserving fashion

Developing and improving ML pipelines for model training, evaluation, and deployment in real-time and batch environments

Continuously monitoring and improving model performance through experimentation and analysis

Leading the iterative and data-driven research and exploration of new approaches for existing or new areas of consideration

Communicating timelines and setting expectations with others under uncertainty

Qualifications

Minimum

MS in Computer Science, Machine Learning, or related fields plus 5 years of experience.

Strong programming skills in Python, with experience in ML frameworks such as PyTorch or Tensorflow

Experience with serving and deploying ML models at scale using various tools such as Spark, Hadoop, etc.

Excellent problem solving and analytical skills, valuing a scientific approach by using experimentation and critical thinking to drive and validate high-quality results

Preferred

PhD

Proficiency in Scala, Java, and/or C++

Proficiency in working with SQL/NoSQL databases

Consistent record of deploying ML solutions validated through relevant industry experiences and/or publications in premier conferences or journals

Experience with geospatial data analysis and modeling

Domain expertise in transportation, navigation, or time series prediction