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Machine Learning Engineer - People Analytics - Apple
ML Engineer
Develop and deploy predictive machine‑learning models for employee data, leveraging Python, deep‑learning frameworks, and cloud services to drive actionable People Analytics insights at scale.
About the role
Key Responsibilities
- Design, build, and productionize predictive models that inform talent acquisition, retention, and performance initiatives.
- Collaborate with data scientists, analysts, and HR stakeholders to translate business questions into robust ML solutions.
- Develop data pipelines and feature engineering workflows using SQL and cloud services to ensure high‑quality, reproducible inputs.
- Implement model monitoring, performance tracking, and automated retraining pipelines on AWS.
- Document methodologies, share best practices, and mentor junior engineers on ML best practices.
Requirements
- 5+ years of professional experience building and deploying machine‑learning models in production.
- Strong proficiency in Python and deep‑learning libraries such as TensorFlow or PyTorch.
- Hands‑on experience with SQL, data warehousing, and building scalable data pipelines.
- Experience deploying ML workloads on AWS (SageMaker, EC2, Lambda, etc.).
- Solid understanding of statistical modeling, feature engineering, and model evaluation techniques.
Skills
pythontensorflowpytorchsqlaws