Machine Learning Engineer - Proactive

Apple is building intelligent search and AI experiences that understand user intent, context, and personal information while preserving privacy. This on-site role in Cupertino, California focuses on semantic retrieval and ranking, embedding and reranking pipelines, and retrieval-augmented generation systems, including efficient on-device model deployment and low-latency inference optimization.

What you’ll do

• Design, optimize, and deploy semantic retrieval systems and ranking models to deliver relevant, personalized, context-aware experiences across Apple’s ecosystem.
• Build systems that combine semantic retrieval, embedding, reranking, and retrieval-augmented generation to improve search quality and AI-powered experiences.
• Enhance the underlying software infrastructure and optimize solutions for low-latency inference.
• Collaborate with engineers, researchers, product managers, and designers to move AI capabilities from research into production, including work on foundation model applications such as multimodal AI, agentic retrieval, and personalized intelligence.

Qualifications

• Minimum: Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Minimum: Background in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI.
• Minimum: Experience with semantic retrieval, embedding models, reranking, or retrieval-augmented generation systems.
• Minimum: 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.
• Preferred: Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Preferred: Experience building and deploying semantic search, retrieval, or ranking systems at scale in a production environment.
• Preferred: Hands-on experience with retrieval-augmented generation, dense retrieval, or neural reranking pipelines.
• Preferred: Experience adapting or distilling large foundation models into compact, efficient models for on-device deployment.
• Preferred: Familiarity with model optimization techniques such as quantization, pruning, or knowledge distillation.
• Preferred: Experience designing and running offline evaluations and online experiments (A/B testing) to measure search quality, ranking, or model performance.
• Preferred: Strong understanding of query understanding, intent modeling, or personalization in search or recommendation systems.
• Preferred: Experience working across cross-functional teams to ship AI-powered features in consumer products.

Tech stack

• Python
• C/C++
• PyTorch
• JAX
• TensorFlow
• A/B testing

Compensation and benefits

The base pay range for this role is $150,400 to $277,600 per year. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.

Benefits include comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and reimbursement for certain educational expenses including tuition. This role may also be eligible for discretionary bonuses or commission payments and relocation.

Additional equity-related benefits include discretionary restricted stock unit awards, and the option to purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.

Location: Cupertino, CA (onsite)