Machine Learning Engineer

Summary

Posted: Sep 12, 2024

Weekly Hours: 40

Role Number:200567466

Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn’t have imagined, and now, can’t imagine living without. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

Description

APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Research, design, and develop computer and network software or specialized utility programs. Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. Develop scalable machine learning infrastructure for applications. Build and integrate end to end lifecycles of large-scale, distributed machine learning systems. Build software that improves rate of experimentation and helps make better decisions about what to try next. Develop tools and services for improving machine learning systems beyond modeling choices. Data distribution editing, data quality improvements to support ML data usage. Architect the end-to-end platform that supports machine learning operations. Collaborate with engineers across functions to solve complex data problems at scale. Identify and evaluate new patterns and technologies to improve performance, maintainability and elegance of machine learning systems. Work with cloud data processing technologies and machine learning modeling frameworks to support application developments. 40 hours/week. 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 $185,752 – $214,500/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: 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: https://www.apple.com/careers/us/benefits.html. 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 Employment Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities.

Minimum Qualifications

• Bachelor’s degree or foreign equivalent in Computer Science or related field and 4 years of experience in the job offered or related occupation.
• 2 years of experience with each of the following skills is required:
• Designing and implementing API backend to build distributed machine learning systems
• Using Python for training and evaluating machine learning models
• Using Java to build micro-services APIs in cloud and infrastructure
• Run large-scale data analytics applications across clustered computers using Spark
• Using relational databases such as MySQL to store and query data
• Using distributed storage systems
• Using high performance query engine for big data including Presto.
• Debugging and monitoring production services

Preferred Qualifications

• N/A