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Internship Rlhf Jobs in New York (NOW HIRING)

Internship Rlhf information

Is there a shortage of ML engineers?

The demand for ML engineers remains high across industries due to the growth of artificial intelligence and data-driven applications. Companies often seek candidates with skills in machine learning frameworks like TensorFlow or PyTorch, and a strong background in programming and statistics, leading to a competitive job market for qualified professionals.

What are Internship RLHF positions?

Internship RLHF positions refer to internships focused on Reinforcement Learning from Human Feedback (RLHF), a cutting-edge area in artificial intelligence research. Interns in RLHF roles typically work on projects that involve training AI models to align with human preferences using feedback data, often in natural language processing or robotics. These internships are usually offered by tech companies or research labs and provide hands-on experience in machine learning, data analysis, and experimental design. RLHF interns often collaborate with experienced researchers and engineers to advance AI systems' safety, reliability, and alignment with human values.

What jobs can I get with human computer interaction?

With a background in human-computer interaction (HCI), you can pursue roles such as user experience (UX) designer, usability analyst, interaction designer, or user researcher. These jobs involve designing and improving digital interfaces, often requiring skills in user research, prototyping, and familiarity with tools like Adobe XD or Figma.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as internships in research, healthcare, and skilled trades, are more likely to survive AI automation. Roles involving emotional intelligence, nuanced decision-making, and hands-on skills are less susceptible to automation. Developing expertise in these areas can improve job security in an internship setting.

What is the difference between Internship Rlhf vs Research Assistant?

AspectInternship RlhfResearch Assistant
Required CredentialsTypically enrolled students or recent graduatesUsually requires a relevant degree or ongoing education in the field
Work EnvironmentInternship programs, often in academic or research institutionsResearch labs, universities, or research-focused organizations
Employer & Industry UsageUsed by educational institutions and research organizations for trainingCommon in academia, government, and private research sectors
Search & Comparison IntentPeople comparing internship opportunities or entry-level research rolesIndividuals seeking research support or entry-level research positions

Internship Rlhf and Research Assistant roles both involve research activities, but internships are typically short-term training positions for students or recent graduates, while research assistants are more formal, often requiring relevant education and supporting ongoing research projects. Understanding these differences helps candidates choose the right opportunity based on their experience and career goals.

Is ML a high paying job?

Machine learning (ML) jobs, including roles like ML engineer or data scientist, tend to offer high salaries compared to many other tech positions due to the specialized skills required, such as programming, statistics, and experience with tools like TensorFlow or PyTorch. Entry-level positions may start lower, but experienced professionals often earn six-figure salaries, especially in industries like finance, tech, and healthcare.

What types of projects and tasks can I expect to work on during an RLHF internship?

As an RLHF (Reinforcement Learning from Human Feedback) intern, you can expect to engage in a variety of projects that combine machine learning, data annotation, and model evaluation. Typical tasks include curating and labeling datasets, training and fine-tuning machine learning models using human feedback, and conducting experiments to evaluate model performance. You may also collaborate closely with engineers and researchers, participate in team meetings, and contribute to documentation or research publications. This hands-on experience will help you develop both technical and collaborative skills essential for a career in AI research.

What are the key skills and qualifications needed to thrive as an RLHF (Reinforcement Learning from Human Feedback) Intern, and why are they important?

To thrive as an RLHF Intern, you need a solid background in machine learning, statistics, and programming (especially Python), usually supported by ongoing or completed studies in computer science or a related field. Experience with deep learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and familiarity with reinforcement learning libraries are typically required. Strong problem-solving abilities, curiosity, and effective teamwork and communication skills help interns contribute meaningfully and learn quickly. These skills and qualities are crucial for successfully developing, evaluating, and improving RLHF models in a collaborative research environment.
What are the most commonly searched types of Rlhf jobs in New York? The most popular types of Rlhf jobs in New York are:
What cities in New York are hiring for Internship Rlhf jobs? Cities in New York with the most Internship Rlhf job openings:
Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)

Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)

Unity Technologies

New York, NY โ€ข On-site

Other

Medical, Life, Retirement, PTO

Posted yesterday


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

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.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

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