Senior ML Engineer, NLG & Summarization: Shape AI Writing

Apple Inc.; Seattle (WA); On-site; USD 175,000 - 309,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Employee stock programs

Relocation assistance

Tuition reimbursement

Job summary

Apple Inc. is seeking a Senior Machine Learning Engineer for the Natural Language Generation group in Seattle. You will own the quality of AI features across multilingual products, shaping pipelines for data synthesis, prompt engineering, and model evaluation.

The role emphasizes on-device deployment readiness, interdisciplinary collaboration, and advancing robust, privacy-preserving language models used by billions of users.

Qualifications

• MS or PhD in Computer Science or related field, or equivalent practical experience.
• History of shipping AI features built on language models.
• Experience building and maintaining model pipelines end-to-end, from data curation/synthesis and LLM judges to post-training.
• Strong Python programming skills, with experience developing production-quality Python modules.
• Excellent written and verbal communication skills.

Responsibilities

• Own the model quality of shipping and unreleased Apple Intelligence features
• Prioritize and drive modeling efforts across multiple fronts
• Analyze user feedback to understand shortcomings of our models and evaluation data
• Define robust evaluation mechanisms to drive data curation, metric calibration, and model hill-climbing
• Research state-of-the-art SFT/PEFT/RLHF/distillation techniques for improving model quality and robustness
• Implement pipelines, experiments, and simulations to assess the value of modeling changes

Skills

Model quality control

Data synthesis

Prompt engineering

LLM evaluation

Python programming

Communication skills

On-device models

Education

MS or PhD in Computer Science or related field

Job description

Apple Inc. is seeking a Senior Machine Learning Engineer for the Natural Language Generation group in Seattle. You will own the quality of AI features across multilingual products, shaping pipelines for data synthesis, prompt engineering, and model evaluation.

The role emphasizes on-device deployment readiness, interdisciplinary collaboration, and advancing robust, privacy-preserving language models used by billions of users.