Staff Machine Learning Engineer

Apple • Cupertino, CA • 6h ago

Weekly Hours: 40

Role Number: 200641090-0836

Summary

We are looking for a Machine Learning Engineer who will be converting abstract, high-level goals into concrete, measurable requirements. They will be proposing, implementing, evaluating, and shipping di?erent AI/ML technologies and resulting data to achieve a given task. This role will be collaborating with various partners, including engineering orgs and designers to architect the best overall system.

Description

As a member of our team, you'll have the opportunity to work with a team of highly skilled engineers and scientists to bring new experiences to Apple Maps! This position requires a self-motivated engineer/scientist with strong technical and interpersonal skills.

Minimum Qualifications

5+ years of experience in building large scale machine learning systems.

Deep understanding of NLP fundamentals including embedding generation, text similarity, entity recognition.

2+ years of experience in one or more of the following ML areas: generative AI models (e.g. Transformers, LLMs, VLMs, etc).

Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Scala, Python, Java, or C++ Experience working with large scale and real world datasets

Knowledge of Spark, Solr/Lucene, Cassandra, and related big data technologies

Metrics focused and passionate about delivering models that render high quality results

Familiarity with cloud platforms such as AWS, GCP, or Azure.

Strong problem-solving, communication, and ability to collaborate with cross-functional teams.

Preferred Qualifications

Understanding of Knowledge graphs and their applications to entity matching

Working knowledge of Deep learning and computer vision, are pluses

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .

Apple

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