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About the Role
Apple Services Engineering (ASE) powers AI and LLM features for millions of users. This role focuses on developing data systems, predictive models, and automation tools to optimize workforce capacity, forecast demand, and enhance evaluation operations into an AI-driven platform.
Responsibilities
- Design, scale, and evolve systems for workforce planning, demand forecasting, spend optimization, and operational telemetry.
- Develop algorithmic forecasting models to manage demand volatility.
- Build conversational, tool-driven workflows for self-service operational decision-making.
- Eliminate operational friction and automate decisions related to resource and capacity constraints.
- Expand the throughput of features evaluation workflows.
- Prototype, validate, and ship practical, scalable tooling for operations leads and engineering partners.
- Translate fragmented operational data streams into unified data models, automated monitoring systems, and actionable decision tools.
- Incorporate user feedback into tooling design.
- Communicate technical concepts clearly to non-technical partners.
- Support Data Operations, Human-in-the-Loop (HITL) annotation pipelines, or AI/ML features evaluation workflows.
- Design internal tools, services, or interfaces that are intuitive, configurable, and extensible.
- Leverage AI, automation, and decision intelligence to scale organizational efficiency.
Requirements
- 3–5+ years of industry experience in applied science, data engineering, or operations research.
- Demonstrated experience building practical data systems or predictive models.
- Strong programming proficiency in Python and SQL.
- Hands-on experience designing, deploying, and maintaining resilient data pipelines and backend utilities.
- Experience developing quantitative or predictive models (e.g., time-series forecasting, resource allocation, capacity planning, or constrained optimization) applied to operational or business problems.
- Experience building or integrating intelligent automation, conversational interfaces, or tool-calling/retrieval workflows using modern LLM APIs.
- Demonstrated experience translating fragmented operational data streams into unified data models, automated monitoring systems, and actionable decision tools.
- Demonstrated ability to work directly with cross-functional users to incorporate feedback into tooling design.
- Demonstrated ability to communicate technical concepts clearly to non-technical partners.
- Familiarity with workflow orchestrators (e.g., Airflow or similar engines) and containerized deployment patterns.
Skills
- Python
- SQL
- Data Systems
- Predictive Models
- Time-series forecasting
- Resource allocation
- Capacity planning
- Constrained optimization
- Intelligent automation
- Conversational interfaces
- LLM APIs
- Data engineering
- Operations research
- FastAPI
- Streamlit
Experience Level
- 3-5+ years
Education Level
- MS or PhD in Computer Science, Data Science, Operations Research, Statistics, or a related quantitative field, or equivalent practical experience.
About the Company
- Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day.
- The ML Data Quality Operations team within Human-Centered AI is looking for an Applied Data Scientist.