Machine Learning Engineer, Data for Foundation Models

Apple Inc.; Cupertino (CA); Hybrid; USD 150,000 - 278,000; Full time

Benefits offered by this job

Relocation assistance

Employee stock purchase plan

Tuition reimbursement

Comprehensive medical and dental cover

Job summary

Apple Inc. is seeking a Machine Learning Engineer focused on Data for Foundation Models in Cupertino.

You will design data pipelines, curate large-scale image/video datasets, and apply synthetic data generation techniques to improve diffusion and autoregressive models used in Apple products. The role requires strong ML fundamentals, hands-on research experience, and expertise with PyTorch/JAX and large-scale data frameworks.

Qualifications

• MS/PhD in Computer Science or related field
• 3+ years improving image generation or understanding models via data ablation
• Experience with ML frameworks (PyTorch/JAX) and large-scale data tools (Hadoop/Ray)
• Experience in academic or industrial research environment
• Excellent communication, bias-for-action, and clarity in ambiguity

Responsibilities

• Design data annotation, enrichment, curation and synthetic data pipelines for foundation models
• Build high-quality datasets for training diffusion or autoregressive models
• Apply and extend genAI tools to improve data quality aligned with Apple products
• Stay at the forefront of AI research and rapidly adopt impactful developments

Skills

ML fundamentals

Data ablation experiments

PyTorch/JAX

Hadoop/Ray

Academic/industrial research

Education

M.S./PhD in CS or related field

Tools

PyTorch

JAX

Hadoop

Ray

Job description

Machine Learning Engineer, Data for Foundation Models

Cupertino, California, United States Machine Learning and AI

Do you believe that generative models can fundamentally change how people interact with devices? Are you excited by the possibility of connecting people to unprecedented levels of creativity? Come join the team that turned cutting edge Generative AI research into compelling user experiences through Apple Intelligence. We are part of the Intelligent System Experiences team at Apple and work on the core modeling technology behind Genmoji, Image Playground and Photos Generative Edits. From web-scale datasets to distributed training of foundation models, application specific adapters to on-device optimizations, you will have the unique opportunity to advance and ship state-of-the-art technology that impacts Apple users around the world!

Description

We are seeking a machine learning research engineer with experience building high-quality datasets for foundation model training. The ideal candidate has solid ML fundamentals, experience with applied research, and hands-on knowledge of constructing large scale and targeted datasets involving image or video to improve the quality of diffusion or auto-regressive foundation models. You will stay at the forefront of the latest AI research to rapidly adopt impactful developments while simultaneously pioneering proprietary and experimental ideas. You will design data annotation, enrichment, curation and synthetic data generation pipelines using classic or genAI tools to improve model quality along specific dimensions aligned with Apple's unique product offerings.

Minimum Qualifications

• M.S. or PhD in Computer Science or a related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience
• 3+ years of experience improving modern image generation or image understanding models through data ablation experiments
• Knowledge of ML frameworks such as PyTorch / JAX. Experience leveraging large-scale data frameworks such as Hadoop / Ray.
• Experience working in an academic or industrial research environment
• Excellent communication skills, bias-for-action and ability to drive clarity in ambiguous circumstances

Preferred Qualifications

• Hands-on experience improving the quality of diffusion image generation models through training data improvements
• Track record of strong industrial research output, shipped complex projects or published at top-tier venues

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 $150,400 and $277,600, 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.