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On-device ML Infrastructure Engineer (Compiler & Runtime)

Apple

On-device ML Infrastructure Engineer (Compiler & Runtime)

Apple

Cupertino, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Wellness benefits

Annual team offsites

Flexible PTO policy

Health, dental, and vision coverage

Top Tier compensation with equity

Required Skills

Airflow

Apache Spark

SQL

On-device ML Infrastructure Engineer (Compiler & Runtime)

3 weeks ago• Cupertino, CA
Apply on company site

About Us

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
Size: 10000+ employees

Industry: Technology, Information Technology, Software, Consumer Goods & Services

Imagine being at the forefront of an evolution where modern AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.

Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding powerful architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple's machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem.

If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful cluster, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents a great opportunity to work on the next generation of intelligent experiences on Apple platforms.

We are seeking an experienced ML Infrastructure Engineer with a specific focus on building the best execution engine and compilation toolchain that employs our compilers infrastructure and the world's most efficient, portable, and extensible runtime, and which is capable of optimizing and driving ML models efficiently on Apple products and services, current and future.

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Description:

We're building an end-to-end developer experience for machine learning development that brings to bear Apple's vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. This is a senior role and functions as the glue between our compiler technology, the runtime components, the kernel libraries, and the low-level hardware compilers to enable the execution of ML across a wide variety of devices and use cases. The successful candidate will make critical decisions affecting project direction and outcome.

We're seeking a highly motivated software engineer who is creative, skilled, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning.","responsibilities":"

Help lead and deliver on critical initiatives for on device machine learning infrastructure.

Design, build, and maintain critical machine learning infrastructure that powers Apple's machine learning features.

Collaborate with downstream hardware compilers to best leverage Apple's machine learning hardware.

Collaborate with first and third party users to adopt our infrastructure and apply protocols when they implement machine learning on Apple devices.

Ensure our infrastructure can run optimally for a wide range of first and third party machine learning models.

Preferred Qualifications

Experience with any on-device ML stack, such as TFLite, ONNX, Execu Torch, etc.

Experience with open source machine learning models (Mistral, Phi, Gemma, Huggingface, etc)

Experience with any compiler stack (MLIR/LLVM/TVM/...).

Experience with any ML authoring framework (Py Torch, Tensor Flow, JAX, etc.).

Experience with machine learning accelerators and GPU programming.

Minimum Qualifications

Bachelors in Computer Science, Engineering, or related subject area and 7+ years of hands on experience.

Highly proficient in C++. Familiarity with Python and Swift.

Familiarity with Operating Systems and Embedded Programming.

Sound understanding of ML fundamentals, including common architectures such as Transformers.

Good communication skills, including ability to communicate with multi-functional audiences.

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. Learn more about your EEO rights as an applicant .

Client-provided location(s): Cupertino, CA

Job ID: apple-200630418-0836_rxr-660

Employment Type: OTHER

Posted: 2026-01-08T19:13:43
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Perks and Benefits

Health and Wellness

Parental Benefits

Work Flexibility

Office Life and Perks

Vacation and Time Off

Financial and Retirement

Professional Development

Diversity and Inclusion

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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

L2

L3

L4

L5

L6

L2 · Business Analyst L2

0 reports

$114,215

total / year

Base

$45,686

Stock

$57,108

Bonus

$11,422

$79,951

$148,480

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit