Engineering Leader, AI Safety Engineering & Evaluation, Apple Services Engineering

Description

Minimum Qualifications

• 12+ years of experience in software engineering, machine learning engineering, applied AI, or related technical disciplines, including demonstrated experience delivering complex production-quality systems.
• 8+ years of engineering or applied machine learning management experience, including at least 3 years managing engineering managers or leading multiple technical teams through established managers.
• Demonstrated experience building or transforming engineering organizations, including developing technical talent, establishing engineering practices, and scaling teams through periods of organizational or technical growth.
• Strong software engineering foundation, including experience guiding architecture, implementation, and operationalization of complex software or AI/ML solutions.
• Practical expertise in machine learning and modern AI architectures, including model development, inference, and evaluation methodologies.
• Strong technical foundation in Python and modern software development practices, with the ability to assess technical tradeoffs and guide engineering execution.
• Demonstrated ability to develop technical roadmaps, establish priorities, manage resources, and deliver measurable outcomes in ambiguous environments.
• Excellent communication and stakeholder management skills, with experience influencing senior technical and cross-functional leaders.
• Bachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience leading teams developing AI/ML evaluation systems, automated model assessment, or applied machine learning solutions.
• Experience with generative AI and large language models, including LLM-based evaluation, agentic systems, model orchestration, or adversarial testing.
• Applied experience with machine learning modeling, statistical analysis, experimental design, and quantitative evaluation methods.
• Experience developing automated model assessors, synthetic data generation, red teaming, or systematic failure analysis capabilities.
• Familiarity with Responsible AI principles and technical approaches to fairness, bias, robustness, harmful content, and safety risk assessment.
• Experience integrating evaluation capabilities into existing engineering platforms, development workflows, or continuous measurement processes.
• Experience leading multidisciplinary engineering organizations through technical transformation, particularly involving automation or applied machine learning.
• Ability to translate emerging research techniques into reliable engineering implementations.
• Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical discipline.