ML Model Quality Engineer – GenAI Data Trust

Apple, Inc.; Cupertino (CA); Presencial; USD 185 000 - 325 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical and dental coverage

Employee stock programs

Tuition reimbursement

Relocation assistance

Resumo da oferta

Apple, Inc. is seeking a Machine Learning Engineer focused on ML model quality and data health for Wallet, Payments, and Commerce.

You will design validation frameworks, observability metrics, and telemetry for GenAI workflows to ensure models are trained, evaluated, and deployed on trustworthy data. You will collaborate with Data Engineering, Privacy, and Legal teams to build robust systems and dashboards that monitor model health across ML and GenAI features used by hundreds of millions of

Qualificações

• Bachelor’s degree or higher in ML/CS/DS/Statistics preferred.
• 3+ years defining and tracking ML model health metrics in production.
• 3+ years in ML/data science with focus on data quality or observability.
• Proficiency in Python, Pandas, NumPy, Scikit‑learn; SQL for data analysis.

Responsabilidades

• Curate and maintain ground-truth datasets for model evaluation and validation.
• Audit training data for bias and fairness; monitor data drift over time.
• Define and analyze telemetry across GenAI workflows and model health signals.
• Design mechanisms to detect degradation of models in production with privacy in mind.
• Define and own ML observability metrics and data quality metrics.
• Develop observability dashboards and reporting workflows for stakeholders.

Conhecimentos

Python & NumPy

PyTorch

SQL

Model health metrics

Statistical methods

Strong communication

Formação académica

Bachelor’s or higher in ML/CS/DS/Statistics

Ferramentas

Tableau

Superset

Databricks

MLflow

Weights & Biases

Descrição da oferta de emprego

Apple, Inc. is seeking a Machine Learning Engineer focused on ML model quality and data health for Wallet, Payments, and Commerce.

You will design validation frameworks, observability metrics, and telemetry for GenAI workflows to ensure models are trained, evaluated, and deployed on trustworthy data. You will collaborate with Data Engineering, Privacy, and Legal teams to build robust systems and dashboards that monitor model health across ML and GenAI features used by hundreds of millions of