Join the Apple Maps team and help shape the future of navigation for hundreds of millions of users worldwide! We are seeking a dedicated ML Engineer to revolutionize our traffic predictions and navigation systems. Your work will directly impact how people move through their world, making their journeys more efficient and enjoyable. This is an ideal position for an engineer with a strong background in supervised, unsupervised, and deep learning techniques who possesses deep intuition and experience in applying statistical modeling techniques to user facing products. If you're passionate about applying ground breaking machine learning techniques to solve sophisticated, real-world problems at a global scale, this is your opportunity to make a difference!
Description
As an ML Engineer on the Apple Maps Navigation team, you'll be at the forefront of developing and optimizing machine learning models that power our traffic predictions and navigation products. Your work will ensure that Apple Maps provides the most accurate and reliable navigation experience possible, while handling and working with high volumes of live and historical data. You'll work as part of a dynamic, multi-functional team of software and ML engineers, data scientists, and traffic experts to help set the future direction of the product. Your responsibilities will include prototyping domain-specific algorithms, rapidly evaluating their quality and leading the production implementation effort. Our collaborative environment encourages knowledge sharing and provides opportunities to work on various aspects of Apple Maps.
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
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Minimum Qualifications
BS in Computer Science, Machine Learning, or related fields
Strong programming skills in Python, with experience in ML frameworks such as PyTorch or Tensorflow
Experience with serving and deploying ML models at scale
Excellent problem solving and analytical skills, valuing a scientific approach by using experimentation and critical thinking to drive and validate high-quality results
Preferred Qualifications
MS/PhD or equivalent experience in Computer Science, Machine Learning, or related fields
Proficiency in Scala, Java, and/or C++
Proficiency in working with SQL/NoSQL databases
Excellent communication skills and ability to adapt quickly in a dynamic, fast-paced environment
Consistent record in machine learning, validated through relevant industry experiences and/or publications in premier conferences or journals
Experience with large-scale data processing systems (e.g., Spark, Hadoop)
Experience with geospatial data analysis and modeling or transportation science
Domain expertise in transportation, navigation, or time series prediction
Experience with cloud technologies and distributed systems
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