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Manager Recommender Systems Jobs (NOW HIRING)

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Manager Recommender Systems information

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$46K

$112K

$197K

How much do manager recommender systems jobs pay per year?

As of Jun 12, 2026, the average yearly pay for manager 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 the difference between Manager Recommender Systems vs Data Scientist?

AspectManager Recommender SystemsData Scientist
CredentialsAdvanced degree in CS, ML, or related field; experience with recommender algorithmsDegree in CS, Statistics, or related; strong programming and analytical skills
Work EnvironmentLeading teams, overseeing recommender system projects, collaborating with product teamsAnalyzing data, building models, interpreting results across various domains
Industry UsageTech companies, e-commerce, streaming services

While both roles require strong technical skills and data expertise, Manager Recommender Systems focus on leading teams and managing recommender system projects, whereas Data Scientists primarily analyze data and develop models across diverse applications.

What are the key skills and qualifications needed to thrive as a Manager, Recommender Systems, and why are they important?

To thrive as a Manager, Recommender Systems, you need a solid background in computer science, machine learning, and data analytics, typically supported by a relevant degree and experience in building recommendation algorithms. Familiarity with programming languages like Python or Scala, machine learning frameworks, and big data platforms such as Spark or Hadoop is essential, along with knowledge of A/B testing and model evaluation techniques. Strong leadership, project management, and cross-functional communication skills distinguish top performers in this role. These skills ensure effective team guidance, robust system development, and alignment of technical solutions with business goals in a fast-evolving digital landscape.

What are Manager Recommender Systems?

A Manager of Recommender Systems is a professional who oversees the development and deployment of algorithms that suggest products, services, or content to users based on their preferences and behavior. They lead teams of data scientists, engineers, and analysts to design, implement, and optimize recommendation engines. Their role involves strategic planning, project management, and ensuring that the recommender systems align with business goals while delivering a personalized user experience.

How does a Manager of Recommender Systems typically collaborate with data scientists and engineers to deliver effective recommendation solutions?

As a Manager of Recommender Systems, you will frequently coordinate cross-functional efforts between data scientists, machine learning engineers, and product teams. Your role involves setting project priorities, facilitating communication to ensure clear understanding of objectives, and removing roadblocks that may impede progress. You’ll also oversee the translation of business requirements into technical solutions, review algorithm performance, and guide the team in iterative model improvements. Regular collaboration ensures that the recommendations delivered align with both user needs and business goals.
More about Manager Recommender Systems jobs
What cities are hiring for Manager Recommender Systems jobs? Cities with the most Manager Recommender Systems job openings:
What are the most commonly searched types of Recommender Systems jobs? The most popular types of Recommender Systems jobs are:
What states have the most Manager Recommender Systems jobs? States with the most job openings for Manager Recommender Systems jobs include:
Infographic showing various Manager Recommender Systems job openings in the United States as of June 2026, with employment types broken down into 90% Part Time, and 10% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.
Research Scientist Graduate (TikTok Recommendation-Large Recommender Models) - 2026 Start (PhD)

Research Scientist Graduate (TikTok Recommendation-Large Recommender Models) - 2026 Start (PhD)

TikTok

San Jose, CA • On-site

$156K - $387K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 28 days ago


TikTok rating

7.6

Company rating: 7.6 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

114th of 188 rated software companies


Job description

Responsibilities
You'll be joining the TikTok Recommendation team focusing on advancing large-scale recommender systems that power TikTok's personalized content discovery and user experiences. By developing cutting-edge models, we aim to optimize recommendation accuracy, user engagement, and scalability across billions of users. We're looking for Machine Learning Scientists passionate about building high-performance, scalable recommendation systems. You'll leverage advanced deep learning techniques and large-scale systems engineering, collaborating with cross-functional teams to solve complex challenges in personalization and recommendation at scale. We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok. Successful candidates must be able to commit to an onboarding date by end of year 2026. We will prioritize candidates who are able to commit to these start dates. Please state your availability and graduation date clearly in your resume. Applications will be reviewed on a rolling basis. We encourage you to apply early. Responsibilities 1. Research and develop large-scale recommender systems for personalized, engaging user experiences, focusing on scalability, accuracy, and performance. 2. Apply advanced machine learning and deep learning techniques to optimize recommendation algorithms for TikTok's diverse user base. 3. Manage the end-to-end lifecycle of recommender models, from training and fine-tuning to deployment, monitoring, and continuous improvement. 4. Analyze complex data to uncover user preferences, behaviors, and trends, driving personalization and enhancing TikTok's recommendation capabilities. 5. Collaborate with cross-functional teams (infrastructure, product, research, etc.) to design and implement innovative solutions that improve the relevance and diversity of TikTok recommendations.
Qualifications
Minimum Qualifications 1. Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. 2. Experience in one or more areas of recommender systems, machine learning, computer vision, or natural language processing. 3. Proficiency in programming skills, solid foundation in data structures and algorithms. 4. Strong familiarity with deep learning architectures such as transformers, CNNs, RNNs, LSTMs, etc. 5. Excellent analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams. Preferred Qualifications 1. Ph.D. in Computer Science, Electrical Engineering, or related fields. 2. Experience in building large-scale recommender systems that handle vast, diverse datasets and complex user interactions. 3. Publications in major AI venues such as RecSys, SIGGRAPH, CVPR, ICCV, ICML, NeurIPS, ICLR, or similar conferences/journals.
Job Information
[For Pay Transparency]Compensation Description (Annually)
The base salary range for this position in the selected city is $156000 - $387600 annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok Accommodation
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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