Machine Learning Engineer (Search)
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Key details
- Location
- United States
- Work style
- Onsite
- Level
- Mid level
- Experience
- 2–5 yrs
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- 2w ago
Skills
About the role
Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging. We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of opportunities to build groundbreaking technologies using Machine Learning and Generative AI at scale to improve the search quality for Apple Maps.
Description
Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging. We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of opportunities to build groundbreaking technologies using Machine Learning and Generative AI at scale to improve the search quality for Apple Maps.
Minimum Qualifications
MS in computer science or equivalent field with 2+ years of industry experience
Proven record in delivering end-user facing Machine Learning driven products
Strong programming experience in one or more of the following: Java, C++, Python
Knowledge and experience with one of Tensorflow/Pytorch/Jax frameworks.
Excellent interpersonal and communication skills - working independently and/or in small teams
Attention to detail, data accuracy and quality of output.
Preferred Qualifications
Ph.D in computer science or equivalent field with 2+ years of industry experience.
Expertise and experience in various facets of machine learning and natural language processing, such as classification, feature engineering, information extraction, clustering, semi-supervised learning, topic modeling and ranking
Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics.
Good knowledge of big data processing, prior experience with Hadoop, Spark, Hive is highly desired.
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