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Online Rlhf Jobs in Virginia (NOW HIRING)

Online Rlhf information

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 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.

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 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 the most commonly searched types of Rlhf jobs in Virginia? The most popular types of Rlhf jobs in Virginia are:
What are popular job titles related to Online Rlhf jobs in Virginia? For Online Rlhf jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Online Rlhf jobs? Cities in Virginia with the most Online Rlhf job openings:
Research Scientist

Research Scientist

University of Virginia

Charlottesville, VA • On-site

Full-time

Posted yesterday


University Of Virginia rating

7.8

Company rating: 7.8 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

196th of 539 rated colleges and universities


Job description

Department Overview
The University of Virginia's Research Computing (RC) team, part of UVA Information Technology Services (ITS), supports cutting-edge research across the institution by providing advanced computational resources and expertise. Within RC, the Data Analytics Center (DAC) enables interdisciplinary collaboration by helping researchers apply modern data science and AI techniques to complex problems.
UVA ITS does more than support the UVA community - we empower and move it forward. With every partnership and every solution, we are shaping a culture and ecosystem where learning and discovery thrive.
Position Summary
The University of Virginia is seeking a Research Scientist with expertise in Large Language Models (LLMs) to join the Data Analytics Center (DAC) within Research Computing. This role will partner directly with researchers across disciplines to apply LLMs and AI techniques to diverse datasets, enabling innovative research outcomes.
As a key member of the Research Computing team, you will contribute technical expertise in deep learning and LLMs, support high-impact research initiatives, and help advance UVA's leadership in data-driven discovery.
Responsibilities
  • Collaborate with researchers to understand datasets and analytical requirements
  • Perform data preprocessing and analysis to identify appropriate deep learning and LLM approaches
  • Select, fine-tune, and apply LLMs and AI models to complex research problems
  • Optimize LLM performance on HPC systems, including parallel implementations
  • Manage AI-based research projects to ensure timely delivery and scientific rigor
  • Prepare technical reports, presentations, and research outputs
  • Develop and deliver training sessions and workshops on LLMs for the UVA community
  • Partner with the DAC team to share programming techniques and best practices
Minimum Qualifications
Education:
Advanced degree (Master's or higher)
Experience:
At least 2 years of relevant work experience
Skills:
  • Proficiency in Python programming
  • Demonstrated expertise in AI systems and machine learning algorithms
  • Strong analytical and problem-solving abilities
  • Excellent written and verbal communication skills
  • Ability to collaborate with researchers across diverse disciplines
  • Strong relationship-building skills with technical and non-technical stakeholders

Additional Requirement:
  • U.S. citizenship or permanent residency required due to access to high-security data environments
Preferred Qualifications
Education:
  • PhD in Computer Science, Electrical Engineering, Data Science, or related field

Experience:
  • 3+ years of academic or applied research experience

Technical Skills:
  • Deep understanding of transformer architectures (attention, tokenization, embeddings, positional encoding, scaling)
  • Experience with fine-tuning techniques (supervised fine-tuning, instruction tuning, RLHF, domain adaptation)
  • Proficiency with AI frameworks such as PyTorch, TensorFlow, and Hugging Face
  • Experience with LLM evaluation and benchmarking methodologies
  • Familiarity with generative or probabilistic modeling

Additional Knowledge:
  • Understanding of LLM risks such as hallucinations and bias, and responsible AI practices
Physical Demands
This is primarily a sedentary role. The position may require the ability to sit for extended periods and use a computer for prolonged durations.
Position Type & Work Location
  • Full-time
  • Located in Charlottesville, VA
  • Flexible work arrangements may be available

This position has committed funding through June 2028; continuation is dependent on the availability of funding.
About UVA and the Community
The University of Virginia is a highly regarded public institution known for its commitment to academic excellence, innovation, and service. Located in Charlottesville, UVA offers a vibrant community with a high quality of life, combining rich history with a dynamic and forward-looking environment.
UVA fosters a collaborative culture that values diversity, equity, and inclusion, and is dedicated to supporting employees' professional growth and work-life balance.
Application Timeline
Review of applications will begin after the position has been posted for a minimum of five days.
Additional Requirements
  • Background check required
  • This position will not sponsor applicants requiring a visa

How to Apply
Please apply online through Online and search for R0081788 . Complete the application and upload the following required materials:
Internal applicants may search and apply for jobs on the UVA Internal Careers website .
  • Cover letter
  • Resume
Reference Check Process
Reference checks will be conducted via UVA's standard SkillSurvey process, requiring a minimum of three completed references.
Contact
For questions about this position, please contact:
Bill Crane
Senior Talent Acquisition Recruiter
University of Virginia
Xer5ff@virginia.edu
MINIMUM REQUIREMENTS:
Education: Bachelor's Degree required.
Experience: 3+ years relevant experience required.
Licensure: None.
PHYSICAL DEMANDS:
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

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About University of Virginia

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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819