Staff Applied Scientist, AI Quality & Meta Evaluation

Apple Inc

Quick summary

Work type
On-site
Location
Seattle, WA
Salary
$201,300–$302,200 / yr
Posted
31 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k
This role $252k
$167k most similar roles pay here $317k

This role pays more than 76% of similar roles. Most pay $191,537–$249,753 — the shaded band above. At the midpoint, this role pays about $252k versus about $221k 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Staff Applied Scientist, AI Quality & Meta Evaluation

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As a Principal Applied Scientist on the Human Centered AI team at Apple Services Engineering, you will lead the technical development of the Data Quality Validation framework, ensuring the reliability and trustworthiness of large language model evaluations. You will design statistical frameworks to detect discrepancies between automated evaluators and human ground truth, develop algorithms for risk-stratified sampling, and establish rigorous standards for immutable ground truth sets. Your role involves hands-on work with Python to build models that audit Production LLM Judge outputs for bias and drift, ensuring new judges are rigorously validated before deployment. This high-impact position requires expertise in uncertainty quantification, model calibration, and anomaly detection, as well as experience with Human-in-the-Loop pipelines and large-scale reasoning models.

Skills

Python Bayesian Uncertainty Quantification Entropy Modeling Statistical Process Control Inter-rater Reliability HITL Active Learning CI/CD Out-of-distribution Detection Large-scale Reasoning Models LLM Evaluation Science

What you'll do

  • Design and develop the reasoning agent that audits Production LLM Judge outputs.
  • Develop statistical and ML approaches to detect divergence from ground truth.
  • Define algorithms for risk-stratified smart sampling in deeper review processes.
  • Establish hierarchical weighting models and confidence interval frameworks.
  • Set standards for building, versioning, and validating immutable ground truth sets.
  • Validate new LLM Judges through standard validation processes before production.
  • Serve as the scientific authority on data quality evaluation methodology for partners.

What we're looking for

  • Master's degree in Statistics, Data Science, Machine Learning, Computer Science, or related quantitative field
  • 8+ years experience in applied data science, ML research, or evaluation science
  • Expertise in uncertainty quantification and model calibration techniques
  • Experience building disagreement detection models in production systems
  • Strong command of statistical measurement frameworks including inter-rater reliability
  • Proficiency in Python for statistical modeling and ML experimentation
  • Ability to translate complex statistical findings into actionable guidance

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