Senior Software Engineer, Machine Learning Infrastructure and Quality

The cloudOS team is responsible for all facets of delivering OS and system services on Apple silicon servers, including driving hardware and software initiatives to enable new Apple silicon-based systems in data centers.

Our Apple Services Engineering team is hiring for an exciting new role as a Senior Software Engineer in Machine learning. We are seeking a highly motivated and detail oriented software engineer to drive innovations in software development and quality for various machine learning workflows. The right candidate for this position is passionate about delivering the best possible experience for our users and is continuously looking for new ways to measure and improve the quality of our software stack and infrastructure. Additionally, having the ability to switch between designing creative product usage scenarios and immersive analysis of detailed feature design will be a critical skill to possess.

Description

This is a full time Software Developer position where you will be driving working on various aspects of machine learning including training, inference, and characterization for various ML workloads. You will also be responsible to define, measure, and improve the quality of machine learning technologies at Apple by developing infrastructure, automation and services which facilitate validation and qualification of these technologies. In addition, you will be responsible for developing and implementing comprehensive automated test plans. You will be working cross-functionally with many teams across Apple impacting all levels of the Apple's machine learning stack. You will be the voice of our customers, championing quality software development through each step of the development process and driving quality improvements throughout the organization.

Preferred Qualifications

5+years using one of the following scripting languages e.g. Python, Go, or JavaScript

5+years of experience working with an building Operating Systems

Minimum Qualifications

5+ years of experience with hardware and/or software development lifecycle processes

5+years of experience in one or more compiled languages (e.g. C, C++, Objective-C/Swift)

Proficient in one or more scripting languages e.g. Python, Go, or JavaScript

Experience with Machine Learning, its common practical applications, and commonly used frameworks

Proven understanding of Operating System concepts

Proven ability crafting, maintaining and implementing tests plans across all application layers

Applying statistical concepts to validate and QA data and models

QA and automation experience involving ML workflows is a huge plus

Posses the capability to accept ambiguity and deliver extraordinary results on tight schedules

B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience

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 $175,000 and $308,500, 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.