ZipRecruiter

Log In

1

Recommender Systems Jobs in California (NOW HIRING)

next page

Showing results 1-20

All JobsRecommender Systems JobsRecommender Systems Jobs in California

Recommender Systems information

See California salary details

$45.4K

$110.5K

$194.4K

How much do recommender systems jobs pay per year?

As of Aug 19, 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.

Senior ML Engineer, Scalable Recommender Systems (San Mateo)

Roblox

San Mateo, CA • On-site

$192K - $238K/yr

Full-time

Re-posted 17 days ago

Job description

A leading gaming platform in San Mateo, CA, is seeking a talented individual to design and implement large-scale recommendation systems. The role requires expertise in machine learning and the ability to translate research into production systems. Ideal candidates will hold a PhD in a relevant field and possess a strong background in recommender systems and large-scale engineering. The position offers an annual salary range of $192,890 — $238,520, with a hybrid work model.
#J-18808-Ljbffr

Apply