Senior Machine Learning Engineer, Proactive

Apple is hiring a Senior Machine Learning Engineer to build next-generation intelligent search and AI experiences that understand user intent, context, and personal information while preserving privacy.

Responsibilities

• Build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems, plus models for query understanding, intent prediction, personalization, retrieval, and ranking.
• Analyze search relevance and user behavior to define evaluation methodologies, including offline benchmarks and online metrics for retrieval quality, ranking, personalization, and language model performance.
• Create scalable experimentation and evaluation pipelines for LLMs and search models, covering model quality, robustness, latency, efficiency, and end-to-end product metrics.
• Design, train, fine-tune, distill, and optimize transformer-based language models and foundation models for efficient on-device deployment.
• Develop LLM fine-tuning and post-training methods including supervised fine-tuning, instruction tuning, preference optimization, parameter-efficient fine-tuning, and task-specific adaptation.
• Research and prototype on-device generative AI approaches such as knowledge distillation, model compression, quantization, pruning, and low-latency inference.
• Transfer capabilities from large foundation models into compact on-device models while balancing quality, latency, memory footprint, power consumption, and compute constraints.
• Partner across engineering, research, product, and design to move AI from prototype to production, shaping technical strategy and exploring applications such as foundation models, multimodal AI, agentic retrieval, and personalized intelligence.

Requirements

• 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 knowledge distillation, compression, quantization, and pruning.
• Experience with on-device machine learning or edge AI, including optimizing for latency, memory, compute, and power constraints.
• Experience distilling capabilities from large foundation models into smaller language models or task-specific models for efficient inference.
• Experience building retrieval-augmented generation, vector search, embedding retrieval, neural reranking, or semantic search systems.
• Experience with query understanding, query rewriting, intent classification, personalized retrieval, learning-to-rank, or recommendation models.
• Experience with transformer architectures and foundation model families including BERT, T5, Llama, Gemma, Mistral, or related architectures.
• Experience evaluating language models, defining AI quality metrics, and building automated and human-in-the-loop evaluation pipelines.
• Experience building large-scale production systems for search, recommendation, personalization, or generative AI.
• Familiarity with multimodal foundation models, tool use, agentic AI, or agentic retrieval systems.
• Strong understanding of tradeoffs among model quality, latency, memory, power consumption, privacy, and reliability for production on-device AI.
• Ability to prototype new ideas, run rigorous experiments, resolve ambiguous technical problems, and translate research into production-quality ML solutions.

Technologies

• Python
• C/C++
• PyTorch
• JAX
• TensorFlow
• transformers
• BERT
• T5
• Llama
• Gemma
• Mistral

Minimum Qualifications

• Master 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.
• Experience with modern deep learning architectures and techniques including transformers, embeddings, representation learning, and neural ranking.
• Programming skills in Python and/or C/C++, with experience building production-quality software using PyTorch, JAX, or TensorFlow.
• Ability to work onsite in Cupertino, California, in accordance with Apple's applicable work policies.

Pay & Benefits

• Base pay range: USD 184,700 - 324,800 per year, depending on skills, qualifications, experience, and location.
• Opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs.
• 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.
• Comprehensive medical and dental coverage.
• Retirement benefits.
• Range of discounted products and free services.
• Reimbursement for certain educational expenses, including tuition, for formal education related to advancing your career at Apple.
• Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
• Note: Benefits, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.