Machine Learning Engineer (LLM)
Location
Cupertino, CA | United States
Job description
Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. Do you want to impact the future of Manufacturing here at Apple through cutting edge ML techniques? This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on ground breaking, new applications of machine learning, research and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products' supply chain.
The goal of Apple's Manufacturing and Operations team is to take a vision of a product and turn it into a reality. Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. We’re looking for experienced machine learning professionals to help us revolutionize how we manufacture Apple’s amazing products. Put your experience to work in this highly visible role.
Key Qualifications
- 5+ years of experience in data analysis and machine learning.
- Solid understanding and experience in machine learning algorithms, statistics, and data mining models.
- Proven experience with transformer models such as BERT, GPT, RoBERTa, etc., and a solid understanding of their underlying principles
- Understand algorithms (be able to tweak them when needed) as well as infrastructure that enables fast iterations.
- Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries.
- Experience working with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, SQL/NoSQL is a plus.
- Ability to meaningfully present results of analyses in a clear and impactful manner. Able to break down sophisticated machine learning model knowledges to digestible information for non-technical audience.
- Proven experience in managing and mentoring teams is a plus.
- Experience in applying ML techniques in manufacturing and testing space is a major plus.
Description
Operations Advanced Analytics team is looking for creative and motivated hands on individual contributors who thrive in dynamic environment and enjoy working with cross functional teams. As a member of our team, you will work on applied machine learning algorithms to seek problems that focus on topics such as classification, regression, clustering, optimizations and other related algorithms to impact and optimize Apple’s supply chain and manufacturing processes. You will work with the team to build end to end machine learning systems and modules, and deploy the models to our factories. You'll be collaborating with Software Engineers, Machine Learning Engineers, Operations, and Hardware Engineering teams across the company.
Education & Experience
PhD or Master of Science degree in Computer Science or similar, alternatively a comparable industry career with a consistent track record of successful projects
Additional Requirements
- Engineering background and manufacturing experiences preferred.
- Experience with ML in manufacturing and operations spaces. In particular, working with massive and messy manufacturing data set, as well as deploying production ready model to the factory.
- Experience with manufacturing and supply chain ML use cases such as testing optimization, cost reduction, and quality improvement.
- Experience with computer vision and deep learning in manufacturing.
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 $138,900.00 and $208,300.00, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 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.
Operations Advanced Analytics team is looking for creative and motivated hands on individual contributors who thrive in dynamic environment and enjoy working with cross functional teams. As a member of our team, you will work on applied machine learning algorithms to seek problems that focus on topics such as classification, regression, clustering, optimizations and other related algorithms to impact and optimize Apple’s supply chain and manufacturing processes. You will work with the team to build end to end machine learning systems and modules, and deploy the models to our factories. You'll be collaborating with Software Engineers, Machine Learning Engineers, Operations, and Hardware Engineering teams across the company. PhD or Master of Science degree in Computer Science or similar, alternatively a comparable industry career with a consistent track record of successful projects
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