Urgent! On-Device ML Infrastructure Engineer (ML User Experience APIs & Integration) Job | Apple
**Weekly Hours:** 40
**Role Number:** 200595557-0836
**Summary**
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.
We are seeking an ML Infrastructure Engineer to focus on ML user experience APIs and Integration.
In this role, which offers terrific exposure to developing new ML model conversion & authoring APIs that will be a part of coremltools (CoreML’s authoring/conversion toolkit), you will also be central to integrating the APIs into internal and external systems (e.g., HuggingFace) to demonstrate the most efficient way of ingesting models into CoreML from these systems.
This integration could involve a gamut of optimizations ranging from authored program optimizations (e.g., in PyTorch), to custom optimizations on CoreML’s model representation.
**Description**
As an engineer in this critical role, you will develop and use APIs in coremltools to enable ML engineers to efficiently author/convert ML models to CoreML.
You will be integrating coremltools into internal and external ML model repositories to evaluate and demonstrate how ML models can ingested into CoreML.
You will ideate, design, and stress test the gamut of optimizations required to ingest these models, ranging from source level optimizations (e.g., in the PyTorch program), to custom optimizations after converting to CoreML’s model representation.
The role requires a good understanding of ML modeling (architectures, training vs inference trade-offs, etc.), ML deployment optimizations (e.g., quantization), and a good understanding of designing Python APIs
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 coremltools authoring and conversion APIs are the entrypoint to the rest of the infrastructure stack.
**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.
+ Understanding of common ML inference optimizations, such as quantization, pruning, KV caching, etc.
**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.
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) .
✨ Smart • Intelligent • Private • Secure
Practice for Any Interview Q&A (AI Enabled)
Predict interview Q&A (AI Supported)
Mock interview trainer (AI Supported)
Ace behavioral interviews (AI Powered)
Record interview questions (Confidential)
Master your interviews
Track your answers (Confidential)
Schedule your applications (Confidential)
Create perfect cover letters (AI Supported)
Analyze your resume (NLP Supported)
ATS compatibility check (AI Supported)
Optimize your applications (AI Supported)
O*NET Supported
O*NET Supported
O*NET Supported
O*NET Supported
O*NET Supported
European Union Recommended
Institution Recommended
Institution Recommended
Researcher Recommended
IT Savvy Recommended
Trades Recommended
O*NET Supported
Artist Recommended
Researchers Recommended
Create your account
Access your account
Create your professional profile
Preview your profile
Your saved opportunities
Reviews you've given
Companies you follow
Discover employers
O*NET Supported
Common questions answered
Help for job seekers
How matching works
Customized job suggestions
Fast application process
Manage alert settings
Understanding alerts
How we match resumes
Professional branding guide
Increase your visibility
Get verified status
Learn about our AI
How ATS ranks you
AI-powered matching
Join thousands of professionals who've advanced their careers with our platform
Unlock Your On Device Potential: Insight & Career Growth Guide
Real-time On Device Jobs Trends in Cupertino, United States (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for On Device in Cupertino, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 35628 jobs in United States and 23 jobs in Cupertino. This comprehensive analysis highlights market share and opportunities for professionals in On Device roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Apple is currently hiring and seeking a On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) to join their team. Feel free to download the job details.
Wait no longer! Are you also interested in exploring similar jobs? Search now: On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) Jobs Cupertino.
An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Apple adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) Jobs United States varies, but the pay scale is rated "Standard" in Cupertino. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) typically include Other General and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
To improve your chances of getting hired for On Device ML Infrastructure Engineer (ML User Experience APIs & Integration), consider enhancing your skills. Check your CV/Résumé Score with our free Resume Scoring Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.
Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) interview at Apple, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Apple's products or services and be prepared to discuss how you can contribute to their success.
By following these tips, you can increase your chances of making a positive impression and landing the job!
Setting up job alerts for On Device ML Infrastructure Engineer (ML User Experience APIs & Integration) is easy with Cupertino | Expertini. Simply visit our job alerts page here, enter your preferred job title and location, and choose how often you want to receive notifications. You'll get the latest job openings sent directly to your email for FREE!
