Senior Machine Learning Engineer, Proactive
At Apple, machine learning powers experiences that anticipate what people need before they ask. We're looking for a Machine Learning Engineer to help build the next generation of intelligent search and AI experiences technology that understands user intent, context, and personal information while preserving privacy. In this role, you'll design, train, optimize, and deploy large language models, semantic retrieval systems, and ranking models that power relevant, personalized, context-aware search across Apple's ecosystem. You'll work at the intersection of search, retrieval, natural language processing, on-device AI, and generative AI to shape the future of intelligent assistants and proactive experiences..
Description
You'll design, train, fine-tune, and optimize transformer-based language models for on-device deployment, and build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems that improve search quality and AI-powered experiences. You'll develop models for query understanding, intent prediction, personalization, and ranking, while researching new approaches to model compression, quantization, and low-latency inference. You'll partner with engineers, researchers, product managers, and designers to bring new AI capabilities from research into production driving technical strategy and leading projects from early exploration through large-scale deployment. This is an opportunity to explore new applications of foundation models, multimodal AI, and agentic retrieval, shaping the next generation of proactive, intelligent user experiences.
Responsibilities:
Design, train, fine-tune, and optimize transformer-based language models for efficient on-device deployment.
Build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems, along with models for query understanding, intent prediction, personalization, and ranking.
Research and prototype approaches for on-device generative AI, including model compression, quantization, knowledge distillation, and low-latency inference.
Analyze search relevance and user behavior to design evaluation methodologies, offline benchmarks, and online metrics that measure retrieval quality, ranking, and language model performance.
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Partner with engineers, researchers, product managers, and designers to bring AI capabilities from research into production, driving technical strategy across projects and exploring new applications of foundation models, multimodal AI, and agentic retrieval.
Preferred Qualifications
Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Experience optimizing machine learning models for resource-constrained environments, including model compression, quantization, pruning, and knowledge distillation.
Experience with on-device machine learning or mobile inference frameworks.
Experience building retrieval-augmented generation, vector search, embedding retrieval, or semantic search systems.
Experience working with transformer architectures such as BERT, T5, Llama, Gemma, Mistral, or other foundation models.
Experience evaluating language models, designing AI quality metrics, and building offline evaluation pipelines.
Experience building large-scale production search, recommendation, or personalization systems.
Ability to prototype ideas, solve ambiguous problems, and deliver production-quality machine learning solutions.
Minimum Qualifications
Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
5+ years of industry or research experience developing machine learning systems.
Background in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI.
Experience training, fine-tuning, or deploying transformer-based models and large language models.
Programming skills in Python and/or C/C++, with experience building production-quality software using modern machine learning frameworks such as PyTorch, JAX, or TensorFlow.
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 $184,700 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.
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
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