ML Infrastructure Engineer - Multimodal Training Tools, SIML
Apple
Cupertino, California
Posted 1 weeks ago
Qualifications
Education
Bachelors, Masters, or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on machine learning; or comparable professional experience
Responsibilities
Primary Duties
- Contributing towards tools for large generative model training including diffusion & autoregressive workflows
- Tools for efficient inference and hosting of models for experimentation and human feedback
- Tooling for model representation and efficient deployment on multiple HW targets incl. Apple Silicon
- Benchmarking, Analyzing and Improving training and inference performance
- Integrating efficient data loading strategies and auto-eval workflows
- CI/CD of base training workstreams
Experience Requirements
Required
Experienced in training / adapting LLM and Diffusion models
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
training / adapting LLM and Diffusion modelsAdvanced Fluency in PyTorchExcellent programming skillsexperience contributing software to large projectsExperience with distributed training of large models
Full Job Description
ML Infrastructure Engineer - Multimodal Training Tools, SIML
Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generative Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day. We are seeking engineers experienced in building tools for training, adapting and deploying large-scale generative models. You will be working alongside a cross-functional team of engineers who own ML infrastructure & algorithms, data scientists, designers, safety and UX engineers.
In this role you will have a deep expertise in ML tooling, with a passion to empower engineers across the ML stack. Responsibilities include:
Minimum Qualifications:
Preferred Qualifications:
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 $181,100 and $272,100, 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.
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.
Apple accepts applications to this posting on an ongoing basis.
Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generative Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day. We are seeking engineers experienced in building tools for training, adapting and deploying large-scale generative models. You will be working alongside a cross-functional team of engineers who own ML infrastructure & algorithms, data scientists, designers, safety and UX engineers.
In this role you will have a deep expertise in ML tooling, with a passion to empower engineers across the ML stack. Responsibilities include:
- Contributing towards tools for large generative model training including diffusion & autoregressive workflows
- Tools for efficient inference and hosting of models for experimentation and human feedback
- Tooling for model representation and efficient deployment on multiple HW targets incl. Apple Silicon
- Benchmarking, Analyzing and Improving training and inference performance
- Integrating efficient data loading strategies and auto-eval workflows
- CI/CD of base training workstreams
Minimum Qualifications:
- Bachelors, Masters, or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on machine learning; or comparable professional experience
- Experienced in training / adapting LLM and Diffusion models
- Advanced Fluency in PyTorch
- Excellent programming skills and experience contributing software to large projects
- Experience with distributed training of large models
Preferred Qualifications:
- Strong ML Fundamentals
- Experience working with large cross-functional and diverse teams.
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 $181,100 and $272,100, 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.
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.
Apple accepts applications to this posting on an ongoing basis.
How to Apply
$88
/ hour
Apple pays $88 for Network Architect in Cupertino, California, with most salaries ranging from $53 to $146. Pay can vary based on role, experience, and local cost of living.
Median
$88
Low
$53
High
$146
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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.





