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Relevance Jobs (NOW HIRING)

Relevance AI

Revenue Operations Lead

San Francisco, CA · On-site

$179K/yr

  • Medical

  • Dental

  • Vision

  • PTO

With Relevance AI, anyone can create and manage intelligent agents that handle workflows, decisions, and collaboration - all within one unified platform. Our technology already powers industry ...

Reddit

Staff Machine Learning Engineer, Notifications Relevance

$230K - $322K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push ...

Relevance Lab

Chatbot Developer

Not only will you enjoy your work life at Relevance Lab, you'll also have the opportunity to grow your skills and career. If you are passionate about driving results, we'd love to talk with you.

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Showing results 21-40

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Relevance information

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$37K

$96.3K

$122K

How much do relevance jobs pay per year?

As of Aug 18, 2026, the average yearly pay for relevance in the United States is $96,278.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $98,500.00 per year, depending on experience, location, and employer.

What is a relevance engineer?

Relevance engineers are professionals who focus on improving the quality and accuracy of search results, recommendations, and content ranking systems. They work with data, algorithms, and user feedback to ensure that users receive the most useful and pertinent information in response to their queries. Their role often involves optimizing search engines, recommendation systems, and personalization algorithms across various digital platforms. Relevance engineers collaborate with data scientists, software engineers, and product managers to continually enhance user experience by delivering relevant and timely results.

How does a relevance engineer typically collaborate with data scientists and product teams to improve search results?

A Relevance Engineer works closely with data scientists to analyze search data, identify patterns, and experiment with algorithms that enhance the accuracy of search results. They also partner with product managers and UX teams to align technical improvements with user needs and business goals. This collaboration often involves regular cross-functional meetings, sharing insights from A/B tests, and iterating on features based on user feedback and performance metrics. Such teamwork ensures that search relevancy enhancements are both technically sound and user-centric.

What are the key skills and qualifications needed to thrive as a relevance engineer, and why are they important?

To thrive as a Relevance Engineer, you need expertise in information retrieval, machine learning, and data analysis, usually demonstrated by a degree in computer science or a related field. Familiarity with search technologies (like Elasticsearch or Solr), A/B testing platforms, and programming languages such as Python is typically required. Strong problem-solving skills, collaboration, and effective communication help individuals stand out in this role. These competencies ensure that search and recommendation systems deliver accurate, user-focused results, directly impacting user satisfaction and business outcomes.

What is the difference between Relevance vs Content Strategist?

AspectRelevanceContent Strategist
Required CredentialsTypically a degree in marketing, communications, or related fieldSimilar credentials, often with additional specialization in content marketing or digital media
Work EnvironmentMarketing teams, digital agencies, media companiesContent marketing teams, digital agencies, media organizations
Employer & Industry UsageUsed across various industries to assess content relevancePrimarily in marketing, advertising, and media sectors
Search & Comparison IntentPeople compare relevance to content strategists to understand roles in content planningOften compared to relevance to clarify scope of content planning vs. content evaluation

Relevance focuses on evaluating how well content or information aligns with user needs, while a Content Strategist develops and manages content plans to meet marketing goals. Both roles overlap in content creation and digital marketing but differ in their primary focus: relevance is about assessment, and content strategists about planning and execution.

What is a relevant job?

A relevant job is one that aligns with a person's skills, experience, and career goals. It typically matches their qualifications and interests, making it suitable for their professional development and job search objectives.
More about Relevance jobs

What job categories do people searching Relevance jobs look for?

The top searched job categories for Relevance jobs are:

Relevance jobs near you
Infographic showing various Relevance job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $96,278 per year, or $46.3 per hour.

Senior Machine Learning Engineer - Ads Relevance & Quality

Apple

Cupertino, CA • On-site

$151K - $199K/yr

Full-time

Re-posted yesterday

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass.
Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!
Apple's Ads team is seeking a highly skilled and motivated Machine Learning Engineer to join the Ads Relevance and Quality team. This team is responsible for ensuring high-quality, trustworthy ad experiences by building intelligent systems to evaluate ad relevance, detect low-quality or offensive content, and optimize user satisfaction.
You'll work at the intersection of applied ML, NLP, and content quality-designing models and systems that understand queries, flag inappropriate content, and raise the bar for ad relevance and user trust across billions of queries and impressions.
Description
You'll play a key role in shaping the future of safe, high-quality advertising at Apple. Your work will help ensure that ads remain useful, relevant, and respectful of our users-supporting Apple's values of privacy, trust, and transparency. You'll collaborate with world-class engineers and researchers, apply cutting-edge ML techniques in real-world systems, and have a direct impact on the experience of millions of users every day.
Minimum Qualifications
4+ years of experience applying machine learning at scale in domains such as ad tech, content moderation, search ranking, or recommendation systems
Strong expertise in natural language processing, including offensive content detection, semantic matching
Experience with Transformer-based architectures (e.g., BERT, DistilBERT) and training pipelines in TensorFlow or PyTorch
Familiarity with fine-tuning Large Language Models (LLMs) for downstream tasks such as classification, content moderation, or semantic relevance
Familiarity with quality and fairness evaluation frameworks (precision, recall, coverage, policy alignment, etc.)
Hands-on experience with A/B testing, experimentation frameworks, and performance debugging in production
Proficiency in Python and SQL
Strong problem-solving and communication skills with a focus on translating abstract trust/safety goals into deployable solutions
MS in Computer Science, Machine Learning, NLP, or a related technical field
Preferred Qualifications
7+ years of experience applying machine learning at scale in domains such as ad tech, content moderation, search ranking, or recommendation systems
PhD in Computer Science, Machine Learning, NLP, or a related technical field
Additional experience in Scala or Java

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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