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Online Rlhf Jobs (NOW HIRING)

Normal Computing

AI Engineer

New York, NY · On-site

$200K - $300K/yr

Research or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, or program synthesis. * Open-source contributions or publications in AI/ML venues. * Skill in ...

Normal Computing

AI Research Engineer

New York, NY · On-site

$300K - $400K/yr

Stay current on LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, and program synthesis. What Makes You A Great Fit: * PhD in CS/AI/ML (or equivalent research experience) with ...

Sciforium

LLM Training Engineer

San Francisco, CA · On-site

$155K - $220K/yr

Design offline + online environments that support RL-style training at scale * Instrument ... Post-training pipelines (SFT, RLHF/RLAIF, preference optimization, eval loops) * Building RL ...

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$17.5K

$40.6K

$86K

How much do online rlhf jobs pay per year?

As of May 29, 2026, the average yearly pay for online rlhf in the United States is $40,596.00, according to ZipRecruiter salary data. Most workers in this role earn between $25,000.00 and $43,500.00 per year, depending on experience, location, and employer.

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

To thrive as an Online RLHF Specialist, you need a strong background in machine learning, reinforcement learning, and data analysis, typically supported by a degree in computer science or a related field. Familiarity with technical tools like Python, PyTorch or TensorFlow, and experience with human feedback systems or annotation platforms are highly valuable. Strong problem-solving, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills. These qualifications ensure the effective training and evaluation of AI models, leading to more accurate and reliable machine learning systems.

What are some common challenges faced by Online RLHF (Reinforcement Learning from Human Feedback) specialists when collaborating with cross-functional teams?

Online RLHF specialists often work closely with machine learning engineers, data annotators, and product managers. A common challenge is ensuring that feedback from human annotators is accurately integrated into model training, which requires clear communication and well-defined annotation guidelines. Additionally, balancing the pace of model updates with the need for high-quality human feedback can be demanding. Effective collaboration and regular syncs are essential to maintain alignment and achieve project goals.

What are Online RLHF jobs?

Online RLHF (Reinforcement Learning from Human Feedback) jobs typically involve helping to train AI models by providing human feedback on their outputs. Workers in these roles might review model responses, rate the quality of generated text, or suggest improvements to help the AI learn to produce better results. These jobs are often remote and can be done part-time or as contract work. They play a crucial role in improving the safety, usefulness, and accuracy of AI systems by aligning them more closely with human preferences.

What is the difference between Online Rlhf vs Online Rlhf?

AspectOnline RlhfOnline Rlhf
CredentialsTypically requires certification in online health coaching or related fieldsTypically requires certification in online health coaching or related fields
Work EnvironmentRemote, online platform-basedRemote, online platform-based
Industry UsageCommon in health and wellness sectorsCommon in health and wellness sectors
Job FocusProviding health guidance and support onlineProviding health guidance and support online

Online Rlhf and Online Rlhf are the same role, often used interchangeably. Both involve providing health and wellness support remotely, requiring similar certifications and working within the online health industry. The key difference is often in terminology rather than job function.

More about Online Rlhf jobs
What cities are hiring for Online Rlhf jobs? Cities with the most Online Rlhf job openings:
What are the most commonly searched types of Rlhf jobs? The most popular types of Rlhf jobs are:
What states have the most Online Rlhf jobs? States with the most job openings for Online Rlhf jobs include:
What job categories do people searching Online Rlhf jobs look for? The top searched job categories for Online Rlhf jobs are:
Online Rlhf jobs near you
Infographic showing various Online Rlhf job openings in the United States as of May 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $40,596 per year, or $19.5 per hour.

AI Engineer

Normal Computing

New York, NY • On-site

$200K - $300K/yr

Full-time

Posted 28 days ago

Job description

Normal Computing | Incredible Opportunities
The Normal Team builds foundational software and hardware that help move technology forward - supporting the semiconductor industry, critical AI infrastructure, and the broader systems that power our world. We work as one team across New York, San Francisco, Copenhagen, Seoul, and London.
Your Role in Our Mission:
We are looking for an AI Engineer to build production systems that understand large technical documents - like chip design specifications - and turn them into code. You'll ship real improvements to customers weekly while pushing the boundaries of what's possible in AI for hardware through reinforcement learning, agentic coding, and exceptional software engineering.
Responsibilities:
  • Lead end-to-end AI development from initial concept through production deployment and iteration.
  • Design and implement LLM-powered solutions that extract meaning from complex technical specifications.
  • Handle multi-modal complexity and explore multi‑agent and RL approaches for agentic code generation and tool‑use.
  • Design strategies to manage latency, output variance, and graceful error handling at scale.
  • Collaborate with product and engineering teams to embed AI capabilities seamlessly into our platform.
  • Guide junior engineers and establish best practices for AI development

What Makes You A Great Fit:
  • Previous experience delivering production AI systems involving language models, preferably involving document understanding and/or agentic workflows.
  • Solid software engineering skills with experience in distributed systems and production-grade code.
  • Proficiency in Python and modern ML frameworks (PyTorch, Hugging Face, transformers.)
  • Hands-on experience with prompt engineering, fine-tuning, and deploying large language models.
  • Ability to wrangle, clean, and preprocess large-scale, heterogeneous datasets.
  • Understanding of AI safety, bias mitigation, and ethical considerations.
  • Ability to explain complex AI concepts to both technical and non-technical stakeholders.

Bonus Points For:
  • Experience deploying AI systems in mission-critical or high-stakes production environments.
  • Experience with cloud platforms (AWS, GCP, Azure) for large-scale AI infrastructure.
  • Research or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, or program synthesis.
  • Open-source contributions or publications in AI/ML venues.
  • Skill in balancing cutting-edge innovation with production reliability and pragmatism.

Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.

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