Machine Learning Engineer - Apple Maps Navigation
Machine Learning Engineer - Apple Maps Navigation
Machine Learning Engineer - Apple Maps Navigation
Machine Learning Engineer - Apple Maps Navigation
Apple Inc
Computer-Hardware
Zürich
- Art der Anstellung: Vollzeit
- 80.500 CHF – 119.500 CHF (von XING geschätzt)
- Vor Ort
Machine Learning Engineer - Apple Maps Navigation
Über diesen Job
Summary
Posted:
Weekly Hours: 40
Role Number:200624052-4170
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
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
At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.
Gehalts-Prognose
Unternehmens-Details
Apple Inc
Computer-Hardware