The Senior Machine Learning Engineer role at Apple Services Engineering focuses on leveraging Generative AI and advanced NLP systems to drive innovation across the Apple ecosystem. The position requires a hands-on technical leader who can take research ideas to production deployment while navigating ambiguity and scale. The engineer will influence foundational intelligence capabilities, including language understanding and growth optimization. This role offers the autonomy and scope expected of senior technical leadership at Apple.

• Ph.D. in Computer Science, Machine Learning, NLP, Statistics, or a related field, or equivalent industry experience delivering production AI systems.
• At least 6 years of experience in an applied research or machine learning role.
• Expert knowledge of deep learning and modern NLP, including transformer architectures and foundation model adaptation.
• Experience with LLM model development, including fine-tuning, instruction tuning, and prompt engineering for domain-specific reasoning.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow, with experience deploying models in production systems.
• Strong understanding of distributed data processing systems and large-scale experimentation.
• Proven ability to communicate research outcomes, architectural decisions, and technical tradeoffs to technical and non-technical stakeholders.
• Hands-on experience with retrieval-augmented generation (RAG) pipelines and vector-based semantic search systems.
• Experience developing personalization, ranking, or optimization algorithms at scale.
• A record of publications in top-tier ML/AI venues or patent filings demonstrating novel research contributions.

• Influence and implement foundational intelligence capabilities across Apple Services.
• Drive high-impact innovation at unprecedented scale using advanced machine learning techniques.
• Communicate research outcomes and architectural decisions to stakeholders.
• Develop and optimize LLM models for domain-specific reasoning.
• Design and implement retrieval-augmented generation pipelines.
• Evaluate models for language quality, relevance, hallucination, and safety.
• Optimize inference techniques such as quantization and model compression.
• Architect and develop reinforcement learning or multi-armed bandit experiment platforms.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.