Senior ML Engineer — Responsible AI & Safety Evaluation

Apple, Inc.; Cambridge (MA); Presencial; USD 166.000 - 292.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Comprehensive medical & dental

Employee stock purchase plan

Relocation assistance

Tuition reimbursement

Descripción de la vacante

Apple, Inc. is seeking a Senior Machine Learning Engineer to drive Responsible AI evaluation for global generative AI products. You will operationalize policy assessments, design datasets, and implement LLM- and human-in-the-loop methods to quantify safety and inclusivity across multi-modal models.

You will collaborate with cross-functional teams to deliver reliable insights, improve feature safety, and support ship/no-ship decisions while upholding Apple’s privacy and quality standards.

Formación

• Graduate degree or equivalent with strong data collection and analysis
• Experience with human-in-the-loop annotation projects and policy/risk assessments
• Proficiency in Python, data analysis, and ML tools
• Ability to communicate with executives and cross-functional teams
• Experience handling sensitive or potentially offensive content

Responsabilidades

• Drive Responsible AI evaluation for global generative AI products
• Operationalize policy and risk assessments into measurable criteria
• Design datasets and develop LLM- and human-in-the-loop analysis methods
• Build robust data pipelines to produce scalable insights for decisions
• Lead and mentor teammates to improve safety metrics and trust

Conocimientos

Python & Pandas

ML & data science

LLM evaluation

Cross-functional collaboration

Experiment design & metrics

Educación

MS/PhD in CS or related field

4+ years post-PhD or 8+ years BA/BS with relevant experience

Herramientas

Visualization libraries

Descripción del empleo

Apple, Inc. is seeking a Senior Machine Learning Engineer to drive Responsible AI evaluation for global generative AI products. You will operationalize policy assessments, design datasets, and implement LLM- and human-in-the-loop methods to quantify safety and inclusivity across multi-modal models.

You will collaborate with cross-functional teams to deliver reliable insights, improve feature safety, and support ship/no-ship decisions while upholding Apple’s privacy and quality standards.