Design experiments, define success metrics, and run rigorous offline and online evaluations (A/B ... Familiarity with LLM fine-tuning techniques (LoRA, RLHF, instruction tuning) and serving ...
Design experiments, define success metrics, and run rigorous offline and online evaluations (A/B ... Familiarity with LLM fine-tuning techniques (LoRA, RLHF, instruction tuning) and serving ...
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?
| Aspect | Online Rlhf | Online Rlhf |
|---|---|---|
| Credentials | Typically requires certification in online health coaching or related fields | Typically requires certification in online health coaching or related fields |
| Work Environment | Remote, online platform-based | Remote, online platform-based |
| Industry Usage | Common in health and wellness sectors | Common in health and wellness sectors |
| Job Focus | Providing health guidance and support online | Providing 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.
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Job description
BeyondTrust is a place where you can bring your purpose to life through the work that you do, creating a safer world through our cyber security SaaS portfolio.
Our culture of flexibility, trust, and continual learning means you will be recognized for your growth, and for the impact you make on our success. You will be surrounded by people who challenge, support, and inspire you to be the best version of yourself.
The Role
We\'re looking for a Staff AI Data Scientist to design, build, and deploy machine learning models and AI-driven solutions that solve complex business problems. You\'ll work at the intersection of applied research, software engineering, and product — turning raw data into actionable insights and intelligent systems that ship to production.
What You’ll Do
- Develop and deploy machine learning models (supervised, unsupervised, deep learning) for production use cases
- Design experiments, define success metrics, and run rigorous offline and online evaluations (A/B tests, holdouts, causal analyses)
- Fine-tune, prompt-engineer, and evaluate large language models for domain-specific tasks
- Partner with data engineering to define the features, datasets, and pipelines needed for model training and inference
- Collaborate with engineering, product, and business teams to translate ambiguous problems into well-scoped modeling solutions
- Build monitoring and evaluation frameworks to track model performance, drift, and fairness over time
- Communicate findings and recommendations to both technical and non-technical stakeholders through clear visualizations and written reports
- Mentor other data scientists and help raise the bar for modeling rigor across the team
What You’ll Bring
- Master\'s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field (or equivalent practical experience)
- 3+ years of hands-on experience building and deploying ML models in production environments
- Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers
- Deep understanding of statistical modeling, experimental design, and evaluation methodology
- Experience with cloud platforms (AWS, GCP, or Azure) for training, serving, and scaling models
- Familiarity with LLM fine-tuning techniques (LoRA, RLHF, instruction tuning) and serving infrastructure
- Experience leveraging AI coding assistants (such as Claude Code, OpenCode, or GitHub Copilot) to accelerate development workflows
Nice To Have
- Background in cybersecurity, identity security, or anomaly detection
- Familiarity with adversarial ML or AI safety research
- Contributions to open-source projects or published research
Better Together
Diversity. Inclusion. They’re more than just words for us. They are the guiding values of how we build our teams, cultivate leaders, and create a culture where people feel connected.
We take care of our employees so they can take care of our customers. Customers who come from all walks of life just like us. We hire incredible people from diverse backgrounds because when we are different together, we are stronger together.
About Us
BeyondTrust is the global identity security leader protecting Paths to Privilege™. Our identity-centric approach goes beyond securing privileges and access, empowering organizations with the most effective solution to manage the entire identity attack surface and neutralize threats, whether from external attacks or insiders.
BeyondTrust is leading the charge in transforming identity security to prevent breaches and limit the blast radius of attacks, while creating a superior customer experience and operational efficiencies. We are trusted by 20,000 customers, including 75 of the Fortune 100, and our global ecosystem of partners.
Learn more at www.beyondtrust.com.
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About BeyondTrust
Sourced by ZipRecruiter
Industry
Software development
Company size
1,001 - 5,000 Employees
Headquarters location
Atlanta, GA, US
Year founded
1985