ML Infrastructure Engineer - Multimodal Training Tools, SIML
Listed on 2026-01-12
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Engineering
AI Engineer, Systems Engineer
ML Infrastructure Engineer - Multimodal Training Tools, SIML
Cupertino, California, United States Machine Learning and AI
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.
DescriptionIn this role you will have a deep expertise in ML tooling, with a passion to empower engineers across the ML stack.
- 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, analysing and improving training and inference performance
- Integrating efficient data loading strategies and auto‑eval workflows
- CI/CD of base training work streams
- 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 Py Torch
- Excellent programming skills and experience contributing software to large projects
- Experience with distributed training of large models
- 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. 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.
Apple accepts applications to this posting on an ongoing basis.
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