AIML Data Engineer

Apple Inc

Confirmed live yesterday High trust

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Work type: On-site
Location: Austin, TX
Posted: 8 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $188k

$122k most similar roles pay here $255k

This listing doesn't post a salary. Most similar roles pay $134,728–$241,750.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · AIML Data Engineer

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The AIML Data Engineer joins the AppleCare Customer Insights team to build and maintain the data infrastructure powering AI-driven customer experience measurement. This role involves designing scalable pipelines to ingest support conversation data, performing feature engineering for model-ready formats, and orchestrating workflows for LLM-based scoring systems. The engineer will also develop telemetry pipelines to monitor performance, accuracy, and concept drift while conducting root cause analysis to translate data into actionable insights. Key technical requirements include proficiency in SQL and Python, experience with cloud platforms like Snowflake or Databricks, and familiarity with orchestration tools such as dbt, Airflow, or Prefect. The role focuses on the specific domain of evaluating generative support experiences through large language models to provide real-time signals regarding how AI-powered support performs across various quality dimensions.

Skills

Python SQL Snowflake Databricks dbt Airflow Prefect Git CI/CD LLM RAG NLP Kafka Tableau Streamlit Great Expectations Monte Carlo ETL ELT

What you'll do

Design and maintain scalable data pipelines to ingest and transform support interaction data for LLM scoring systems.
Engineer features and perform metadata enrichment to prepare conversation data for AI consumption.
Build telemetry pipelines to track model performance, scoring accuracy, and concept drift across evaluation dimensions.
Develop and operate automated pipeline orchestration workflows to ensure reliable delivery of data across AIML workstreams.
Implement monitoring, alerting, and quality checks for pipeline health, data freshness, and scoring latency.
Conduct root cause analysis to determine if metric shifts are driven by data issues, model changes, or customer behavior.
Partner with program managers to perform targeted investigations and quantify the impact of specific support experiences.

What we're looking for

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
4+ years of experience in data engineering or analytics engineering.
Strong proficiency in SQL and Python for both data engineering and analytical investigation.
Experience with cloud data platforms such as Snowflake or Databricks.
Experience with ETL/ELT tools and pipeline orchestration like dbt, Airflow, or Prefect.
Experience with version control (Git) and CI/CD practices.
Demonstrated ability to conduct root cause analysis and translate findings into actionable recommendations.
Experience building data pipelines for LLM-based systems including RAG, scoring, and evaluation.