On-device ML Infrastructure Engineer (ML Compiler Frontend)

Apple; Cupertino (CA); On-site; USD 143,000 - 265,000; Full time

Job summary

A leading company in technology is seeking an On-device ML Infrastructure Engineer in Cupertino, California to work with the latest machine learning models and frameworks. The role involves onboarding ML architectures to CoreML and developing efficient compilation pipelines. This opportunity offers a competitive salary, comprehensive benefits, and the chance to impact products enjoyed by millions.

Benefits

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Educational reimbursement

Qualifications

• Experience with ML authoring frameworks (PyTorch, TensorFlow, JAX).
• Strong understanding of common ML architectures (e.g., Transformers).
• Familiarity with ML compilers (MLIR/LLVM) is a plus.

Responsibilities

• Develop technologies to onboard new ML models to the on-device stack.
• Architect CoreML's model representation for efficient execution.
• Define optimizations for on-device ML deployment.

Skills

Python

C++

ML Fundamentals

Communication

Education

Bachelors in Computer Science or Engineering

Job description

On-device ML Infrastructure Engineer (ML Compiler Frontend)

**Cupertino, California, United States**

**Software and Services**

**Summary**

Posted: **May 22, 2025**

Weekly Hours: **40**

Role Number: **200605982**

The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products.

The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple’s critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.

Our group is looking for an ML Infrastructure Engineer, with a focus on ML model semantics and frontend stages of ML compilation. The role is responsible for working with ML research and Applied research engineers to onboard the newest ML architectures to CoreML’s ML model representation, including evolving the representation to support the latest and greatest features in the authored ML program (e.g., PyTorch), and develop the frontend stages of CoreML’s model compilation pipelines.

**Description**

As an engineer in this role, you will be primarily focused on the ingestion and optimization of ML programs from different authoring frameworks (such as PyTorch) into CoreML using a combination of graph capture, conversion, and compilation pipelines.

We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple’s vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The ML model representation and frontend compilation is the entrypoint to this stack.

KEY RESPONSIBILITIES:
- Develop technologies to quickly onboard new ML models to our on-device stack, including contributions to ML authoring frameworks.

- Understand different ML operations, architectures, and graph representations in different authoring frameworks. Keep abreast of latest innovations in this space.

- Architect and build CoreML’s model representation that can efficiently represent program semantics from the authored frameworks, while allowing for peak execution performance.

- Define and develop optimizations such as quantization, operator transformations, fusions, etc. to make models more amenable to efficient on-device deployment

**Minimum Qualifications**

+ Bachelors in Computer Sciences, Engineering, or related discipline.

+ Highly proficient in Python programming, familiarity with C++ is required.

+ Proficiency in at least one ML authoring framework, such as PyTorch, TensorFlow, JAX, MLX.

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

+ Familiarity with ML and/or traditional compilers.

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

**Preferred Qualifications**

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

+ Experience with designing Python APIs and production deployment of python packages is a strong plus.

+ Experience with HuggingFace or any other model repository is a strong plus.

+ Experience with MLIR/LLVM or any compiler toolchains is a strong plus.

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

**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 $143,100 and $264,200, 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. (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 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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.