Machine Learning Engineer
Apple
Qualifications
Education
Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent industry experience
Responsibilities
Primary Duties
- Contribute to pre-training data curation for LLM development across all domains and modalities (e.g., web, STEM, code, multilingual, image, audio, video)
- Design, implement, and deploy scalable ML models for information extraction, data selection, and synthetic data generation over trillions of unstructured records
- Design, execute, and analyze scientific experiments to advance our understanding of large language models
- Independently lead small-scale research projects while contributing to cross-functional, larger-scale research initiatives
- Accelerate workflows by building high-quality data tooling that improves data velocity, reliability, and scalability
- Apply expertise in one or more of the following areas: multimodal generation and perception (text, image, video, or audio), OCR, data scaling laws, or data mixing
About This Role
The Machine Learning Platform Technology team is building groundbreaking technology for search, natural language processing, artificial intelligence, and machine learning.
Experience Requirements
Required
4+ years of experience with large language models (LLMs), large multimodal models (LMMs), computer vision, or related AI/ML technologies
4 years of experience
Benefits & Perks
Benefits Package
- Comprehensive medical and dental coverage
- retirement benefits
- a range of discounted products and free services
- reimbursement for certain educational expenses including tuition
Required Skills
Technical Skills
Soft Skills
Full Job Description
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Do you want to make Siri and Apple products more intelligent for our users? The Machine Learning Platform Technology team is building groundbreaking technology for search, natural language processing, artificial intelligence, and machine learning. Our infrastructure and research for data curation form the backbone of Apple Intelligence. It powers the largest Apple foundation models on servers and a wide gamut of services at Apple including Apple Search, Apple Music, AppleTV, AppStore, iMessages, Photos & Camera, Spotlight, Safari, Siri, and upcoming ever exciting Apple products serving millions of queries every day with incredible low latencies, drawing every ounce of compute from our hardware. As part of this group, you will work with one of the most exciting high-performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day. You will have a chance to work on optimizing billions of parameter language and vision and speech models using state-of-the-art technologies and make it run at the scale of Apple.
We design, build, and maintain large-scale ML systems that make petabytes of data easy to process and query while upholding Apple's rigorous privacy standards, for training the next generation of Apple Foundation Models.
Responsibilities
- Contribute to pre-training data curation for LLM development across all domains and modalities (e.g., web, STEM, code, multilingual, image, audio, video)
- Design, implement, and deploy scalable ML models for information extraction, data selection, and synthetic data generation over trillions of unstructured records
- Design, execute, and analyze scientific experiments to advance our understanding of large language models
- Independently lead small-scale research projects while contributing to cross-functional, larger-scale research initiatives
- Accelerate workflows by building high-quality data tooling that improves data velocity, reliability, and scalability
- Apply expertise in one or more of the following areas: multimodal generation and perception (text, image, video, or audio), OCR, data scaling laws, or data mixing
Minimum Qualifications
- 4+ years of experience with large language models (LLMs), large multimodal models (LMMs), computer vision, or related AI/ML technologies
- Experience developing and evaluating machine learning models, with a strong understanding of data and model quality
- Strong programming skills and hands-on experience using one or more deep learning frameworks, such as PyTorch, TensorFlow, or JAX
- Experience building large-scale machine learning systems and working with distributed data processing frameworks
- Strong problem-solving skills with a results-oriented mindset
- Experience leading rapid prototyping and proof-of-concept development for AI/ML applications
- Excellent communication skills, with the ability to work independently and collaborate effectively with cross-functional teams
- Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent industry experience
Preferred Qualifications
- Experience developing or advancing state-of-the-art LLMs and/or LMMs
- Experience with modern deep learning architectures, including Transformers, mixture-of-experts (MoE), and multimodal models
- Experience deploying and scaling machine learning and deep learning models, including VLMs, for production-scale inference
- Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ICCV, AAAI, KDD) and/or demonstrated significant industry impact in AI
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 $216,200 and $324,800, 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.
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. At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here in our culture, our benefits, and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple's workplace. Learn about reasonable accommodations for job applicants. Apple accepts applications to this posting on an ongoing basis.
Company Culture
Work Environment: At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly.
How to Apply
Apple pays $199 for Computer Scientist in Sunnyvale, California, with most salaries ranging from $133 to $308. Pay can vary based on role, experience, and local cost of living.
Companies Similar to Apple for Jobs
Share This Job
Figures represent approximate ranges and may vary based on experience, location, and other factors. For the most accurate information, please consult the employer directly. Contact us to suggest updates to this information.





