The Video Engineering Data Analytics and Quality group is seeking a technical lead with expertise in evaluating machine learning and deep learning models. This role involves designing evaluation frameworks and mentoring a team of engineers and scientists. The candidate will work closely with Apple's research, engineering, and product teams to enhance the quality of AI experiences. A strong analytical mindset and proficiency in Python are essential for success in this position.

• BS degree and a minimum of 10 years relevant industry experience.
• 4+ years of industry or academic experience in machine learning or data science.
• 2+ years of experience leading technical projects or mentoring junior engineers or scientists.
• Strong experience evaluating supervised, unsupervised, and deep learning models.
• Hands-on experience with LLMs such as GPT, Claude, or PaLM.
• Familiarity with multimodal models and their evaluation challenges.
• Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of statistical testing, sampling, and metrics such as precision/recall, BLEU, ROUGE, and FID.
• M.S. or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field.
• Prior experience managing or tech-leading a team of two or more engineers or scientists.
• Experience with open-source evaluation tools such as OpenEval or LLM-as-a-Judge frameworks.
• Familiarity with prompt engineering, few-shot, or zero-shot evaluation techniques.
• Experience evaluating generative models, such as text or image generation systems.
• Prior contributions to ML benchmarks or public evaluations.
• Strong communication and documentation skills.

• Design robust evaluation frameworks for machine learning models.
• Mentor a team of engineers and scientists in technical projects.
• Drive alignment across research, engineering, and product teams.
• Set the technical direction for measuring and improving AI quality.
• Evaluate the performance of various machine learning models.
• Utilize LLMs for scoring and judging mechanisms.
• Collaborate with cross-functional teams to enhance AI experiences.
• Provide feedback in a collaborative environment.

• 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.