Senior Applied Scientist - AI Evaluation & Quality Systems

Apple Inc

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$139,500–$258,100 / yr
Posted
56 days ago
Nearby
99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $206k
This role $199k
$125k most similar roles pay here $272k

This role pays less than 57% of similar roles. Most pay $166,400–$246,150 — the shaded band above. At the midpoint, this role pays about $199k versus about $206k for comparable roles.

Based on 240 similar postings.

Employer

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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist - AI Evaluation & Quality Systems

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As a Senior Applied Scientist at Apple Services Engineering, you will join the Human-centered AI, Data Quality Operations team to develop scalable quality control solutions for AI evaluation systems. Your day-to-day responsibilities include designing ground truth generation pipelines, building calibration frameworks, developing anomaly detection systems, and deploying autonomous QA agents that ensure data accuracy and relevance across various annotation modalities and automated evaluation processes. You will work closely with cross-functional teams to maintain high standards of evaluation quality and communicate findings effectively to both technical and non-technical stakeholders. This role requires expertise in Large Language Models, evaluation methodology for generative AI, and hands-on experience with Python and relevant ML frameworks. The ideal candidate has a strong background in applied science or machine learning, with a focus on human-in-the-loop systems at scale.

Skills

Python ML frameworks Large Language Models Evaluation methodology LLM-as-a-judge Meta-evaluation Failure mode analysis Human-in-the-loop evaluation Ground truth generation pipelines Anomaly detection systems Drift detection Distribution analysis Systematic bias identification CI/CD

What you'll do

  • Design and implement scalable ground truth generation pipelines for varied tasks and annotation types.
  • Build calibration frameworks to maintain evaluator alignment with human judgment over time.
  • Develop anomaly detection systems to identify quality issues in evaluation processes.
  • Create autonomous QA agents for generalizable use across teams and use cases.
  • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders.

What we're looking for

  • 5+ years of industry experience in applied science or machine learning with significant impact on shipped systems.
  • Expertise in designing ground truth generation pipelines and anomaly detection systems for large-scale evaluation.
  • Strong hands-on experience with Large Language Models (LLMs) including prompt engineering and various use cases.
  • Proficiency in Python and relevant ML frameworks, with production experience deploying LLM-based solutions.
  • Working knowledge of human-in-the-loop evaluation systems and methodologies for generative AI quality control.
  • MS or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.

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