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Internship Recommender Systems Jobs (NOW HIRING)

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Internship Recommender Systems information

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$42

How much do internship recommender systems jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for internship recommender systems in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Recommender Systems vs Data Analyst?

AspectInternship Recommender SystemsData Analyst
Required CredentialsTypically a background in computer science, data science, or related fields; familiarity with machine learning and recommender algorithmsDegree in statistics, mathematics, or related fields; proficiency in data analysis tools and programming languages
Work EnvironmentTech companies, startups, or online platforms focusing on personalized recommendationsBusiness, finance, healthcare, or marketing sectors analyzing data to inform decisions
Employer & Industry UsageUsed by companies developing recommendation engines for internships or job matching platformsEmployed across various industries to interpret data, generate reports, and support strategic decisions

Internship Recommender Systems focus on developing algorithms to match candidates with internships, requiring technical skills in machine learning. Data Analysts interpret and analyze data to support business decisions, often using statistical tools. While both roles involve working with data, their applications and skill sets differ significantly.

What are internship recommender systems?

Internship recommender systems are digital tools or algorithms designed to help students and job seekers find internship opportunities that best match their skills, interests, and qualifications. By analyzing user profiles, preferences, and sometimes even past experiences, these systems suggest internships that are likely to be a good fit. They often use machine learning or artificial intelligence techniques to personalize recommendations and improve the matching process over time. Such systems are widely used by universities, career platforms, and large organizations to streamline the internship search and application process.

What types of projects can I expect to work on during an internship focused on recommender systems?

As an intern working on recommender systems, you’ll typically contribute to projects such as improving recommendation algorithms, analyzing user interaction data, and testing new personalization features. You might also collaborate with data scientists and engineers to prototype and evaluate models, conduct A/B tests to measure recommendation performance, and help refine data pipelines. The work often involves both independent research and teamwork, giving you exposure to a blend of technical implementation and real-world problem-solving in a collaborative environment.

What are the key skills and qualifications needed to thrive as an Internship Recommender Systems Engineer, and why are they important?

To excel as an Internship Recommender Systems Engineer, a strong background in computer science, statistics, and machine learning, often supported by relevant coursework or experience, is essential. Familiarity with programming languages like Python, data analysis libraries, machine learning frameworks (such as TensorFlow or PyTorch), and recommendation system algorithms is typically required. Analytical thinking, problem-solving skills, and the ability to collaborate effectively with teams help candidates stand out. These skills are crucial for designing, implementing, and optimizing recommendation systems that deliver accurate and personalized suggestions to users.
More about Internship Recommender Systems jobs
What cities are hiring for Internship Recommender Systems jobs? Cities with the most Internship 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 Internship Recommender Systems jobs? States with the most job openings for Internship Recommender Systems jobs include:
Infographic showing various Internship Recommender Systems job openings in the United States as of June 2026, with employment types broken down into 6% Internship, 33% As Needed, 50% Part Time, and 11% Nights. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Machine Learning Engineer Intern (Global E-Commerce Content Recommendation) - 2026 Summer (BS/MS)

Machine Learning Engineer Intern (Global E-Commerce Content Recommendation) - 2026 Summer (BS/MS)

TikTok

San Jose, CA • On-site

$45 - $60/hr

Internship

Medical, Life

Posted 10 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
Team Introduction Global E-Commerce Content Recommendation team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven. We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at TikTok. Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible. Please state your availability clearly in your resume (Start date, End date). Summer Start Dates: - May 11th, 2026 - May 18th, 2026 - May 26th, 2026 - June 8th, 2026 - June 22nd, 2026 Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. In this role, you'll have the opportunity to: - Drive the development of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem. - Explore generative recommendation techniques, including Diffusion Models, prompt learning, and multimodal content generation, to unlock new capabilities in content discovery. - Build multi-model and cross-scenario systems enabling unified recommendation across livestreams, short videos, and search. - Deliver impactful, end-to-end machine learning solutions that tackle high-priority product challenges related to content understanding, LLMs, robustness, and fairness. - Own and optimize the full-stack ML pipeline-from algorithm design to system infrastructure-to continuously push the boundaries of recommendation performance. - Collaborate with cross-functional teams to craft innovative product strategies and develop intelligent solutions that fuel TikTok's growth in key global markets.
Qualifications
Minimum Qualifications: - Currently pursuing a Bachelor's or Master's degree with a background in computer science, machine learning, or similar fields; - Good knowledge of theoretical and empirical research in addressing research problems; - Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,TensorFlow) and familiarity with deep neural network architectures. - Able to commit to working for 12 weeks during Summer 2026 Preferred Qualifications: - Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product; - Strong first-author publications record in AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.); - Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design; - Internship experience in an AI research organization. Privacy Statement By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy
Job Information
[For Pay Transparency]Compensation Description (Hourly) - Campus Intern
The hourly rate range for this position in the selected city is $45- $60.
Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.
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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