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Internship Rlhf information

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How much do internship rlhf jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for internship rlhf in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is an internship RLHF?

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 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 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 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.

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Infographic showing various Internship Rlhf job openings in the United States as of August 2026, with employment types broken down into 7% Internship, 67% Full Time, 25% Part Time, and 1% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

Technical Product Marketing Engineer, Metropolis - New College Grad 2026

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA has been redefining computer graphics, accelerated computing, and AI for more than 25 years - an outstanding legacy of innovation fueled by groundbreaking technology and phenomenal people. Today, we are tapping into the boundless potential of Physical AI to reshape the systems that run the real world. With NVIDIA Cosmos and Metropolis, we are bringing vision and Agentic AI to the physical world through robotics and smart infrastructure that can perceive, reason and act.
We are looking for an outstanding Technical Marketing Engineer to join the Metropolis team in Santa Clara, CA. The Metropolis team ships on a steadfast cadence, with category defining capabilities using the Cosmos model for video and image generation, video reasoning, robotics, visual agents and AI blueprints - reaching developers and customers in every release. You will join a small, autonomous team of creators that thrives on cracking new problem spaces and shipping the answer, compressing the cycle from emerging problem to working prototype in a week, and to a flagship demo in front of customers and on the GTC stage shortly after. If you bring deep technical mastery, an enthusiast's instinct for the room, an AI-native build style, and the ambition to see your name on the product direction your work drives, we want to hear from you!
What You'll Be Doing:
  • Invent and ship the demos, agents, and reference applications that headline Cosmos launches, GTC keynotes, and flagship customer engagements - agentic Vision AI, multi-agent workflows, video understanding, VLM pipelines, and model fine-tuning.
  • Move from whiteboard sketch to customer concepts and prototype in days, using agentic IDEs and AI-native coding tools as your default development environment.
  • Engage directly with customers, partner developers, and the global developer ecosystem - understanding their workflows, pressure points, and roadmaps, and translating that signal into the next reference design.
  • Develop training toolkits, demo scripts, reference architectures, technical blogs, and whitepapers that empower the global sales force, partner engineers, and the broader developer community.
  • Represent NVIDIA at GTC, industry conferences, webinars, and partner events, and author the bylined posts that accompany the demos you ship.
  • Partner with product management and product marketing on go-to-market and developer-engagement strategy for powerful Cosmos capabilities.
  • Collaborate closely with the architecture, research, libraries, tools, product management, and system software engineering teams at NVIDIA to influence next-generation Cosmos models.
  • Drive product capabilities and roadmap shifts into Cosmos, with your contributions named and visible across Product, Research, and Engineering - credited product influence is a core deliverable of this role, not a side effect.
  • Travel is required for on-site customer visits, conferences, and developer events (30%)

What We Need to See:
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience) with relevant internships.
  • Strong experience within applied AI spanning VLMs, agentic frameworks, model training and fine-tuning, and modern agent orchestration (e.g., NVIDIA Agent Toolkit, LangGraph, MCP).
  • Fluency with agentic IDEs and AI-assisted coding workflows, which you treat as the primary engine for shipping high-fidelity prototypes and production-grade code at speed - anchored by strong coding fundamentals that let you drop below the abstractions when the work demands it.
  • A bias toward building: when you don't know how something works, your first move is to prototype a small version of it. Public demos, GitHub repos, or shipped projects speak louder than slides.
  • Outstanding communication and customer-empathy skills - you genuinely enjoy being in front of developers, customers, and conference audiences, and you bring fresh ideas and a point of view to every conversation.
  • Comfort with the unknown and a high-agency operating mode: given a one-sentence problem statement, you return with a working artifact and a crisp argument for what to build next.
  • Brings original ideas to the team - a brainstorm partner who arrives with a take, not a status update.
  • A track record of turning customer signal into pioneering product outcomes - features, models, or roadmap shifts that exist because you advocated for them.

Ways to Stand Out from the Crowd:
  • Hands-on experience across NVIDIA's Physical AI and agentic stack - Cosmos, Metropolis, Nemotron, NVIDIA Agent Toolkit, NIM, AI Blueprints,, DeepStream, Isaac, and Omniverse.
  • Shipped agentic Vision AI applications in production - multi-agent orchestration, tool use, agent skills, and evals.
  • Foundation model post-training experience (SFT, RLHF, distillation) for vision and multi-modal models.
  • A public footprint - repos, demos, or talks - that reflects an AI-tool-native development style.
  • A demonstrable record of customer focused product influence - features, models, or roadmap shifts traceable to your work.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 92,000 USD - 155,250 USD for Level 1, and 116,000 USD - 184,000 USD for Level 2.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US