Machine Learning Systems Engineer

Apple Inc.; Washington; On-site; USD 131,500 - 243,300; Full time

Benefits offered by this job

Employee stock options

Comprehensive health benefits

Innovative working environment

Job summary

A leading technology company is seeking a Machine Learning Systems Engineer to build the software stack for large machine learning models on Apple Silicon. The ideal candidate will have practical experience in evaluating ML models and optimizing system-level code, paired with a strong background in programming languages like Python, Swift, C, and C++. This role offers a competitive salary range between $131,500 and $243,300, along with opportunities for stock options and professional development.

Qualifications

• Produce reliable, maintainable deliverable software.
• Comfortable diving deep across multiple levels of abstraction.
• Collaborate well with colleagues across a wide range of functions.

Responsibilities

• Build software stack to run large machine learning models over multiple high-performance Apple Silicon SoCs.
• Write software in Swift, Python, and C++ for services and infrastructure.
• Expand software capabilities to build innovative products.

Skills

Practical experience running and evaluating machine learning models for quality and performance metrics

Experience in system-level code optimization and power/performance evaluation for ML acceleration hardware

Large-scale server-side development experience

Programming in Python

Programming in Swift

Programming in C

Programming in C++

Experience with iOS/macOS

Experience with XCode

Education

B.S. in Computer Science or other numerate subject with 6+ years of experience

M.S. in Computer Science or other numerate subject with 4+ years of experience

Job description

Machine Learning Systems Engineer

Summary: Our team is responsible for building libraries and services that form the foundations of critically important systems at Apple. As a ML Systems Engineer, you will focus on building software stack to run large machine learning models (generative AI, LLMs) over multiple high-performance Apple Silicon SoCs.

Key Qualifications

• Practical experience running and evaluating machine learning models for quality and performance metrics
• Experience in system-level code optimization and power/performance evaluation for ML acceleration hardware
• Large-scale server-side development experience
• Experience programming in: Python, Swift, C, C++, iOS/macOS, XCode
• Bonus qualification: familiar with Apple ML stack (ANE, CoreML, MPS/Metal), high-level general distributed ML stack (PyTorch-distributed, NCCL), and high-throughput inter-chip communication systems

Description

We write software in Swift, Python, and C++ to build services and infrastructure around innovative generative AI and machine learning. Our software has a growing user base, and the team is looking to expand to build amazing products, making it a truly exciting place to work.

We’re a collection of highly skilled and friendly engineers who value each other’s opinions and experience. We strive for excellence and believe strongly in the quality of our output.

Education & Experience

B.S. in Computer Science or other numerate subject with 6+ years of experience, or M.S. in Computer Science or other numerate subject with 4+ years of experience

Additional Requirements

• Quality focus - produce reliable, maintainable deliverable software
• Comfortable diving deep - working across multiple levels of abstraction
• Good at handling relationships & communication - collaborate well with colleagues across a wide range of functions

Apple is an equal opportunities employer and welcomes applications from all qualified candidates, including minorities, women, protected veterans, and individuals with disabilities.

Pay & Benefits

The base pay range for this role is between $131,500 and $243,300, 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.