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Apple Generative AI Applied Scientist Machine Learning United States, Washington, Seattle 703585458
11.07.2024
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Description
As an AML applied ML scientist, you will engage with Business Teams: Collaborate closely with business teams to identify opportunities, gain a deep understanding of their requirements, and effectively translate these requirements into innovative technical solutions.
Minimum Qualifications
- 5+ years of industry experience with strong ML fundamentals
- Hands-on experience with building Deep Learning applications
- Proficiency in using ML toolkits, e.g., PyTorch
- Strong analytical and problem solving skills
- M.S. or PhD in Electrical Engineering/Computer Science, or a related field (mathematics, physics, statistics or computer engineering) preferred
Preferred Qualifications
- Strong software engineering skills in Python to create scalable and robust infrastructure for deep learning data, modeling, and evaluation systems
- Proven ability to train and debug deep learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework
- Familiarity with researching current ML literature and math including optimization methods and modeling techniques
- Strong experience in the transition of a prototype into a final product
- Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $161,700 and $284,900, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.
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