Machine Learning Engineer, AI Innovator
3 weeks ago
About the Role:
We are seeking an exceptional Machine Learning Engineer, Applied Machine Learning to join our team. As a key member of our Data Science group, you will work on developing cutting-edge machine learning models that serve various Apple lines of business and enrich end-user experiences.
Responsibilities:
- Develop and implement state-of-the-art machine learning algorithms to enable current and future products and services in various enterprise scenarios.
- Collaborate with large-scale data sets with intensive hands-on code development.
- Work closely with business teams in articulating research methodologies and results.
- Partner with engineering teams in integrating and deploying ML models to deliver amazing user experiences.
Requirements:
- Bachelor's degree in Computer Science, Engineering, or similar quantitative field with a focus on machine learning.
- 3+ years of industry experience implementing end-to-end data science and machine learning projects.
- Familiarity with software development and release cycles.
- 2+ years of experience in one or more of the following ML areas: Computer Vision, NLP, gen AI, AR/VR, Document Intelligence.
- 2+ years of experience in algorithm design, modeling, or quantitative analysis.
- Experience with deep learning frameworks such as PyTorch, TensorFlow, and Keras.
- Experience with optimization, approximation algorithms, distributed algorithm design, and hands-on implementation of these techniques.
Preferred Qualifications:
- MS or Ph.D., Computer Science, Engineering, or similar quantitative field with a focus on machine learning is strongly preferred.
About Us:
Apple 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.
Estimated Salary: $166,600 - $296,300 per year, depending on skills, qualifications, experience, and location.
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