Machine Learning Resource Management Engineer - SIML

Apple; Seattle (WA); On-site; USD 171,000 - 259,000; Full time

Job summary

A leading technology company in Seattle is seeking a Machine Learning Resource Management Engineer to enhance resource management for machine learning systems. The ideal candidate will have over 5 years of experience in supporting scalable ML infrastructures, and proficiency in Python and C++. This role offers a base salary range of $171,600 to $258,100 and the opportunity to participate in employee stock programs.

Benefits

Employee stock programs

Comprehensive benefits package

Qualifications

• 5+ years of proven experience in leading infrastructure strategy for scalable ML systems.
• Experience in engineering resource management.
• Experience in web development is preferred.

Responsibilities

• Contribute to improvements on resource management from a technical and policy standpoint.
• Influence the company on resource management aspects.

Skills

Proficient in Python

Proficient in C++

Strong communication skills

Interpersonal skills

Understanding of fundamental machine learning concepts

Education

Bachelors or Master’s degree in Computer Science, Engineering, or equivalent experience

Tools

Software automation

Job description

Machine Learning Resource Management Engineer - SIML

Seattle, Washington, United States

Machine Learning and AI

Summary

Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling vital to create these exciting technologies.

Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..).

Description

Our team focuses on building the best possible ecosystem for ML R&D engineers to build Apple-quality ML-based technologies. We develop numerous tools to facilitate development of ML models and collaboration around these ML models, and we manage the use of multiple resources such as training compute for Software Engineering, or disk footprint of on-device ML models throughout our operating systems.

In this role: you will focus on the resource management role of our team. You will be tasked to contribute to improvements on how we manage these resources from a technical and policy standpoint, and how we influence the rest of the company on these aspects.

Minimum Qualifications

• Bachelors or Master’s degree in Computer Science, Engineering, or equivalent experience
• 5+ years of proven experience in leading infrastructure strategy to support scalable, high-performance ML systems across storage, compute, networking, and benchmarking
• Proficient in Python and/or C++
• Validated experience in engineering resource management with strong communication and interpersonal skills
• Experience in software automation
• Understanding of fundamental machine learning concepts

Preferred Qualifications

• Proven organizational skills in order to establish durable processes
• Experience in web development
• Deep curiosity in what ML workloads and ML models do, in order to be able to assess them and the associated resource requirements

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 $171,600 and $258,100, 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 is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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.