Senior ML Engineer, Client Experimentation

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 38 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k

This role $255k

$162k most similar roles pay here $342k

This role pays more than 83% of similar roles. Most pay $197,631–$254,750 — the shaded band above. At the midpoint, this role pays about $255k versus about $226k 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 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 · Senior ML Engineer, Client Experimentation

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The Senior ML Engineer - Client Experimentation joins the Ads ML Experimentation team to build next-generation software platforms and systems that advance experimentation for machine learned algorithms at scale. This role involves developing a multivariate experimentation platform, extending it to the client edge for on-device execution, and designing tools for A/B testing, exploratory analysis, and real-time monitoring while preserving user privacy. The candidate will manage SDK-based feature flagging, remote configuration, deterministic bucketing, and telemetry pipelines from device to backend. Required skills include expertise in experimentation frameworks, statistics, and data analysis techniques. The role requires proficiency in Java, Scala, Python, and SQL to solve problems within the advertising domain, specifically focusing on predictive algorithms, recommender systems, and information retrieval while ensuring consistent client-server allocation and robust performance under real-world network conditions.

Skills

Machine Learning A/B Testing Python Java Scala SQL Experimentation Frameworks iOS Data Analysis Statistics Telemetry Pipelines Remote Configuration Feature Flagging Differential Privacy Recommender Systems Information Retrieval Observability

What you'll do

Build and evolve multivariate experimentation platforms to support machine learned algorithms at scale.
Design and engineer tools for managing A/B tests, exploratory analysis, and real-time monitoring.
Develop client-side experimentation features including SDK-based feature flagging and on-device experiment assignment.
Implement telemetry pipelines to log client-side exposure events and metrics from devices to the backend.
Manage staged rollouts, holdbacks, kill-switches, and forced-treatment overrides for client features.
Ensure privacy-preserving measurement through on-device aggregation and minimized data transmission.
Maintain consistency between client/server allocations across different app versions and network conditions.
Translate complex technical analysis into actionable insights to drive product roadmap decisions.

What we're looking for

Degree in Computer Science, Statistics, Applied Math, or a related field.
10+ years of industry experience designing, building, maintaining, and extending web-scale production systems.
Strong experience in experimentation frameworks, A/B testing, and machine learning methodologies.
Proficiency in programming languages including Java, Scala, Python, and SQL.
Experience building client-side experimentation including SDK-based feature flagging and on-device experiment assignment for iOS or similar platforms.
Proven track record of instrumenting client-side exposure and metric logging under real-world network and lifecycle conditions.
Hands-on experience operating staged rollouts, holdbacks, kill-switches, and forced-treatment overrides for client features.
Familiarity with statistics and data analysis techniques to evaluate data quality and business metrics.