Job Description

Apple is committed to harnessing the power of artificial intelligence (AI) to drive innovation and efficiency. We are seeking a skilled and experienced Senior AI Engineer to join our Product Marketing Finance team. This role will focus on developing and deploying AI infrastructure, selecting and fine-tuning models, and building custom AI solutions that support various business functions, including Marketing, Finance, and Customer Analytics. The Senior AI Engineer will be responsible for assessing, designing, developing, fine-tuning, operationalizing, and scaling AI models and solutions that integrate with various data systems and repositories across Apple. This role involves a combination of AI engineering and operational responsibilities, ensuring the successful deployment and scalability of AI models to meet business needs.

Description

Design, develop, and maintain AI platforms to support the deployment of large language models (LLMs) and other AI solutions. Implement scalable and efficient AI systems, ensuring high performance, reliability, maintainability in production environments. Develop, fine-tune, and deploy AI models, including LLMs and NLP models, tailored to specific business requirements. Optimize model performance through hyperparameter tuning, feature engineering, and iterative testing and learning. Collect, preprocess, and analyze large datasets to train and fine-tune AI models. Ensure data quality and integrity throughout the AI model development lifecycle. Monitor the performance and response success of deployed AI models and systems, ensuring they meet business objectives and KPIs. Continuously improve AI systems through performance optimization and applying innovative solutions. Collaborate with cross-functional teams, including data scientists, machine learning specialists, data engineers, and business stakeholders, to integrate AI solutions into business processes. Communicate complex AI concepts and model outputs to non-technical stakeholders in a clear and actionable manner.

Minimum Qualifications

• 4+ years of experience in developing and deploying AI models, particularly large language models and NLP techniques.
• Graduate degree required in Computer Science, Statistics, Data Mining, Machine Learning, Analytics, Econometrics, Mathematics, Operations Research, Industrial Engineering, or related field.

Key Qualifications

Preferred Qualifications

• Proficiency in programming languages such as Python.
• Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or spaCy.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with CI/CD tools and practices for AI model deployment.
• Ability to analyze large datasets and extract meaningful insights using advanced statistical methods.
• Solid technical database and data modeling knowledge (Oracle, Snowflake, Hadoop), and experience optimizing SQL queries on large dataset.
• Outstanding written, verbal, and presentation skills with the ability to develop and present conclusions and recommendation.
• Team player who enjoys collaborating with others to create solutions.

Education & Experience

Additional Requirements

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

Design, develop, and maintain AI platforms to support the deployment of large language models (LLMs) and other AI solutions. Implement scalable and efficient AI systems, ensuring high performance, reliability, maintainability in production environments. Develop, fine-tune, and deploy AI models, including LLMs and NLP models, tailored to specific business requirements. Optimize model performance through hyperparameter tuning, feature engineering, and iterative testing and learning. Collect, preprocess, and analyze large datasets to train and fine-tune AI models. Ensure data quality and integrity throughout the AI model development lifecycle. Monitor the performance and response success of deployed AI models and systems, ensuring they meet business objectives and KPIs. Continuously improve AI systems through performance optimization and applying innovative solutions. Collaborate with cross-functional teams, including data scientists, machine learning specialists, data engineers, and business stakeholders, to integrate AI solutions into business processes. Communicate complex AI concepts and model outputs to non-technical stakeholders in a clear and actionable manner.

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