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Recommender Systems Jobs (NOW HIRING)

Meta

Software Engineer, Recommendation Systems

New York, NY · On-site

$271K - $347K/yr

Meta is seeking a distinguished engineer to help define the future of recommendation systems that serve billions of people across Facebook, Instagram, Reels, Marketplace, and other Meta surfaces. In ...

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How much do recommender systems jobs pay per year?

As of Aug 27, 2026, the average yearly pay for recommender systems in the United States is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $136,000.00 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.

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States with the most job openings for Recommender Systems jobs include:

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Recommender Systems jobs near you
Infographic showing various Recommender Systems job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.

Senior Data Scientist, Recommender Systems

Cincinnati, OH • On-site

Judge Group, Inc.
Recruiting and Staffing Services • 5 - 10K employees
Learn more about Judge Group, Inc.external

$60 - $80/hr

Other

Re-posted 6 days ago

Job description

Location: Cincinnati, OH Salary: $60.00 USD Hourly - $80.00 USD Hourly Description: Our client is currently seeking a Senior Data Scientist, Recommender Systems
Requirements
  • 2+ years of proven experience building deep learning models for large-scale recommender systems.
  • Proficiency in ML frameworks such as TensorFlow or PyTorch.
  • Proficiency in SQL, Python and Spark for data analysis and manipulation. Experience working with Databricks is a plus.
  • Proficiency with statistics, design of experiments, exploratory data analysis, and insights generation.
  • Experience working with cloud platforms like Azure or Google Cloud Platform.
  • Experience working with Data Engineering and MLOps is desirable.
  • High level of independence to develop and own toolkits, pipelines, and dashboards.
  • Excellent problem-solving skills and a proactive approach to addressing challenges.
  • Strong analytical and critical thinking skills with attention to detail.
  • Prior experience in the retail or e-commerce industry is a plus.
  • Must be able to learn from others and teach others and work collaboratively as part of a highly interdependent team.
  • Ability to communicate complex ideas effectively to both technical and non-technical stakeholders.

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