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Internship Recommender Systems Jobs (NOW HIRING)

$45 - $60/hr

... systems, and platforms. Our work supports the fast iteration and incubation of TikTok's recommendation products. We are looking for talented individuals to join us for an internship in 2025.

$42.75/hr

Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ... Drive the development of industry-leading recommendation systems that elevate user experience ...

$68 - $97/hr

... systems. We are looking for people with a general-intelligence mindset to redefine recommendation with us.We are looking for talented individuals to join us for an internship. PhD internships at Our ...

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Internship Recommender Systems information

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How much do internship recommender systems jobs pay per hour?

As of Sep 5, 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 an 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.

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.

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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 August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 9% Part Time, 4% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Machine Learning Engineer, Next-Generation Recommendation Systems

Unitytech

New York, NY • On-site, Remote

$127K - $191K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 4 days ago


Key responsibilities

  • Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.

  • Develop user understanding systems such as conversion prediction, behavioral modeling, and value estimation that operate across billions of impressions.

  • Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.


Job description

The opportunity
Unity's Vector AI team builds the machine learning systems that decide which ads reach which players - across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale.

We are building the next generation of these systems. The frontier has shifted - large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter.

What you'll be doing

  • Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
  • Develop user understanding systems - conversion prediction, behavioral modeling, and value estimation - that operate across billions of impressions.
  • Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
  • Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
  • Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
  • Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.

What we're looking for

  • PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
  • Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
  • Experience working with large-scale data and ML systems, whether through research or industry internships.
  • Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • A track record of rigorous, high-quality research - publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
  • Strong written and verbal communication skills - able to make complex ideas accessible across technical and non-technical audiences.

You might also have

  • Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
  • Hands-on experience with production ML pipelines - training at scale, feature engineering, or experimentation infrastructure.
  • Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
  • Familiarity with agentic AI approaches - multi-step reasoning, tool use, or human-AI collaboration frameworks.
  • Exposure to causal inference, uplift modeling, or A/B testing at scale.
  • Genuine curiosity about applied research and the drive to see ideas through to impact.

Additional information

  • Relocation support is not available for this position
$127,400.00 - $191,200.00

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.

Benefits


At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.


Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.


While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity


Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.


Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.


This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law.


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