Summary Join our Apple Services Special Projects Team and help build the next generation of GenAI solutions for millions of people, upholding the user privacy and security that Apple customers know and expect!
Our team shapes the future of Apple's technologies, experiences, and services by building state-of-the-art models, infrastructure, and tools. If you want a collaborative environment where your expertise is valued, and you want to work on hard generative AI and retrieval problems that haven't been solved, this may be a role for you. We are especially interested in scientists who care about what and how models learn, and who use that understanding to make models more accurate, efficient, and robust.
Description We are seeking a Machine Learning Scientist with a strong track record in applied AI research. You will train and improve the models behind large-scale search, retrieval, and ranking systems, and turn the latest research into production-ready models.
Responsibilities
Train and fine-tune retrieval models: dense embedding models, late-interaction (multi-vector) models, and cross-encoder rerankers, with and without instruction conditioning. Fine-tune and adapt LLMs: including small, efficient LLMs for understanding, judgment, and evaluation tasks, using techniques such as LoRA/PEFT, distillation, and preference optimization (RLHF, DPO). Build training data: design training-data pipelines, including contrastive pairs, hard-negative mining, LLM-generated synthetic data, and data-quality analysis. Develop evaluation frameworks: measure retrieval and ranking quality (nDCG, recall, MRR) and model behavior, with automated and reproducible pipelines. Improve efficiency: analyze model internals and use quantization, pruning, and distillation to improve inference speed and cost without losing quality. Scale training and inference: run distributed training and high-throughput inference on GPU clusters, working with engineers on production serving. Collaborate cross-functionally: partner with ML scientists, engineers, and product teams from concept to launch. Communicate: present results to technical and leadership audiences, and contribute to the research community where appropriate.
Minimum Qualifications PhD in Computer Science, Machine Learning, or a related field, or MS with 5+ years of applied ML research experience Strong deep learning and NLP fundamentals, with hands-on experience training and fine-tuning transformer models Proficiency in PyTorch and strong Python programming skills Experience with post-training, fine-tuning, or representation learning for large models Experience designing rigorous experiments and evaluations, and analyzing model behavior Demonstrated ability to turn research ideas into working systems
Preferred Qualifications
- Experience training embedding, retrieval, or reranking models (e.g., contrastive learning, late-interaction / ColBERT-style models, cross-encoders)
- Experience with parameter-efficient fine-tuning (LoRA, QLoRA, PEFT) and preference optimization (RLHF, DPO)
- Experience with distributed training (e.g., FSDP, DeepSpeed) and multi-GPU workloads Experience with inference engines and serving frameworks (vLLM, SGLang, Triton) Experience with model efficiency: quantization, pruning, distillation, or analysis of model internals Experience with data-centric ML, such as data curation, data attribution, or training-data robustness Familiarity with cloud environments (AWS or GCP) and containerization (Docker, Kubernetes) Publications at top venues (e.g., NeurIPS, ICLR, ICML, CVPR, ACL), and service as a reviewer or program committee member
Pay & Benefits 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.
EEO Statement 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
Accessibility 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.
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Learn about reasonable accommodations for job applicants
Application Deadline Apple accepts applications to this posting on an ongoing basis.
