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Recommender Systems information

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How much do recommender systems jobs pay per year?

As of Aug 20, 2026, the average yearly pay for recommender systems in California is $110,529.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,600.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a recommender system?

A Recommender Systems job involves designing, building, and optimizing algorithms that suggest relevant content, products, or services to users based on their preferences and behavior. Professionals in this field work with machine learning, data science, and engineering to develop personalized recommendations for platforms like e-commerce sites, streaming services, and social media. They analyze large datasets, fine-tune models, and collaborate with cross-functional teams to improve user experiences and drive business goals.

What does a recommender system do?

Professionals in Recommender Systems typically spend their days designing, developing, and optimizing algorithms that suggest personalized content or products to users. Their tasks often involve analyzing large datasets, implementing and testing machine learning models, and collaborating closely with engineers, data scientists, and product managers to deploy these solutions. Regularly reviewing user feedback and system metrics is also important for continuous improvement. The role often requires balancing technical work with cross-team communication to ensure the recommended systems align with overall business objectives.

What are the key skills and qualifications needed to thrive in recommender systems?

To thrive in a Recommender Systems role, you need a strong background in computer science, machine learning, statistics, and data analysis, often supported by a relevant degree or equivalent experience. Familiarity with programming languages such as Python or Scala, frameworks like TensorFlow or PyTorch, and experience with big data tools and collaborative filtering algorithms are typically required. Excellent problem-solving abilities, communication skills, and the capacity to work collaboratively with cross-functional teams are invaluable soft skills. These competencies are vital to designing effective recommendation algorithms that enhance user experiences and deliver business value.

What are the most commonly searched types of Recommender Systems jobs in California?

The most popular types of Recommender Systems jobs in California are:

What are popular job titles related to Recommender Systems jobs in California?

For Recommender Systems jobs in California, the most frequently searched job titles are:

What job categories do people searching Recommender Systems jobs in California look for?

The top searched job categories for Recommender Systems jobs in California are:

Recommender Systems jobs near you
Infographic showing various Recommender Systems job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 7% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $110,529 per year, or $53.1 per hour.

TLM (Tech Lead Manager) - Recommendation Systems (Homepage)

Roblox

San Mateo, CA • On-site

Full-time

Posted 7 days ago

Job description

Engineering Manager, Home Infrastructure

The Home Infrastructure team builds the mission-critical backend and data systems that power Roblox's Homepage and Experience Details Page, two of the highest-traffic surfaces on Roblox. These surfaces reach the vast majority of Roblox's daily active users and are core drivers of discovery, engagement, retention, and platform growth.

We are a full-stack product infrastructure team responsible for content distribution across Roblox. Our systems support multiple modes of user interaction, including exploratory browsing, directed discovery, and personalized content recommendations across the many types of content that make up the Roblox ecosystem.

This team sits at the intersection of large-scale distributed systems, machine learning-powered personalization, data infrastructure, and product experimentation. We partner closely with Machine Learning, Data Science, Product, Design, Frontend, Ads, Marketplace, Virtual Economy, and other teams across Roblox to build the platforms that help users find the most relevant and engaging content.

As Engineering Manager for Home Infrastructure, you will lead a team of Backend and Data Engineers responsible for the end-to-end infrastructure powering Roblox's most important discovery surfaces. You will guide the team's technical strategy, grow engineering talent, and drive execution on high-impact systems that operate at massive scale.

You Will

  • Lead and grow a high-performing team of Backend and Data Engineers responsible for the infrastructure powering Roblox's Homepage and other Discovery product surfaces.
  • Define and execute the technical roadmap for large-scale content discovery, personalization, ranking, data, and backend-serving systems.
  • Drive high-impact initiatives such as Personalization-as-a-Platform, full-page personalization, real-time user signal infrastructure, and ranking observability.
  • Partner closely with Machine Learning, Data Science, Product, Design, Frontend, Ads, Marketplace, Economy, Search, and Core Infrastructure teams to deliver measurable product impact.
  • Build a strong engineering culture focused on technical excellence, reliability, experimentation, operational health, and talent development.

You Have

  • 3+ years of experience as an Engineering Manager or Tech Lead Manager, ideally leading backend, data, ranking, recommendation, search, ads, or personalization teams.
  • Strong technical depth in distributed systems, service-oriented architecture, high-throughput backend platforms, data infrastructure, or ML-powered serving systems.
  • Experience leading teams that build and operate large-scale, consumer-facing production systems with high reliability and performance requirements.
  • A track record of delivering complex, ambiguous, cross-functional technical initiatives with measurable product or business impact.
  • Experience growing engineers, developing technical leaders, and building healthy, high-performing engineering teams.

You Are

  • Technical and strategic: Able to guide architecture, roadmap, and execution across complex backend, data, and personalization systems.
  • Impact-oriented: Focused on building systems that improve user experience, creator success, and Roblox's long-term growth.
  • Data-driven: Comfortable using metrics, experimentation, and evidence to guide product and engineering decisions.
  • Collaborative: Effective at partnering across Product, ML, Data Science, Design, and engineering teams to align priorities and drive outcomes.
  • A talent multiplier: Invested in coaching engineers, raising the engineering bar, and creating an environment where the team can do its best work.

Apply