As a Machine Learning Engineer, you will design and build advanced AI and machine learning systems that deliver significant business outcomes. You will collaborate with other engineers to create scalable, production-ready ML solutions, taking algorithms from concept to deployment. The role emphasizes the development of end-to-end AI/ML solutions with a focus on feasibility, scalability, and performance. You will also integrate AI/ML models into existing systems and ensure their effective deployment.

• 8 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.
• Bachelor's Degree in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or a related field.
• Proficiency in one or more object-oriented programming languages such as Python, Java, or C++.
• Experience building large-scale machine learning systems using big data technologies such as Spark, SQL, or Snowflake.
• Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with MLOps practices including model versioning and CI/CD pipelines.
• Experience building and deploying applications using large language models via APIs or self-hosted inference.
• Hands-on experience with agentic frameworks such as LangChain or LlamaIndex.
• Solid understanding of ML fundamentals including supervised and unsupervised learning.
• Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML solutions.
• Excellent cross-functional communication skills.

• Design and build cutting-edge AI/ML systems that drive meaningful business outcomes.
• Collaborate with other MLEs to build scalable, production-ready ML solutions.
• Benchmark, adapt, and integrate AI/ML models into existing systems.
• Ensure the deployment of robust, production-grade machine learning solutions.
• Focus on the feasibility, scalability, and performance of AI/ML solutions.
• Collaborate effectively across engineering and data science teams.

• 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.