San Francisco, CA · On-site
Designing and training systems using RLHF, RLAIF, and reward modeling approaches, applied to scientific hypothesis generation and evaluation. * Process reward models and verifiers: Developing fine ...
San Francisco, CA · On-site
Designing and training systems using RLHF, RLAIF, and reward modeling approaches, applied to scientific hypothesis generation and evaluation. * Process reward models and verifiers: Developing fine ...
... RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. • Analyze Model Reasoning: critically assess how an AI model navigates ...
... RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness. • Analyze Model Reasoning: critically assess how an AI model navigates ...
Post-train LLM agents using RLHF, DPO, GRPO, PPO, and emerging methods * Build pipelines that convert human-labeled traces and verifiable signals into training data * Architect multi-turn, tool-using ...
Post-train LLM agents using RLHF, DPO, GRPO, PPO, and emerging methods * Build pipelines that convert human-labeled traces and verifiable signals into training data * Architect multi-turn, tool-using ...
San Francisco, CA · On-site
The world's leading AI labs use Rapidata to generate RLHF training data, run model evaluations, and collect human preference signals that make their models better. Founded in 2023 and headquartered ...
San Francisco, CA · On-site
The world's leading AI labs use Rapidata to generate RLHF training data, run model evaluations, and collect human preference signals that make their models better. Founded in 2023 and headquartered ...
TD(0), TD(λ), eligibility traces, bootstrapping methods LLM Alignment & Post-Training • RLHF pipelines: Reward model training, preference learning, human feedback integration • Direct ...
TD(0), TD(λ), eligibility traces, bootstrapping methods LLM Alignment & Post-Training • RLHF pipelines: Reward model training, preference learning, human feedback integration • Direct ...
Lead the design and execution of alignment pipelines (SFT, RLHF, RLAIF) that bridge the gap between "exam-passing" models and "clinically useful" systems. • Leverage Proprietary Data: Utilize our ...
Lead the design and execution of alignment pipelines (SFT, RLHF, RLAIF) that bridge the gap between "exam-passing" models and "clinically useful" systems. • Leverage Proprietary Data: Utilize our ...
$140K - $160K/yr
SFT data curation, preference data collection for RLHF/DPO, golden datasets, custom benchmarks, LLM-as-judge pipelines, human-in-the-loop evaluation, red teaming, and multimodal eval (text, image ...
$140K - $160K/yr
SFT data curation, preference data collection for RLHF/DPO, golden datasets, custom benchmarks, LLM-as-judge pipelines, human-in-the-loop evaluation, red teaming, and multimodal eval (text, image ...
Seattle, WA · On-site
$300K - $500K/yr
Develop and scale post-training methods such as PPO, GRPO, DPO, rejection sampling, RLHF/RLAIF, online RL, and model-based data improvement. * Design the systems abstractions that connect research ...
Seattle, WA · On-site
$300K - $500K/yr
Develop and scale post-training methods such as PPO, GRPO, DPO, rejection sampling, RLHF/RLAIF, online RL, and model-based data improvement. * Design the systems abstractions that connect research ...
The team publishes regularly and ships findings into RLHF pipelines and evaluation suites. PhD or equivalent in ML / economics / decision theory expected. Posted on the board of The Incentives Lab ...
The team publishes regularly and ships findings into RLHF pipelines and evaluation suites. PhD or equivalent in ML / economics / decision theory expected. Posted on the board of The Incentives Lab ...
Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and ...
Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and ...
Fine-tune open-source LLMs using LoRA, RLHF, DPO, and model distillation techniques. * Implement model evaluation pipelines and benchmark reporting. * Collaborate with Prompt & Data teams to create ...
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Fine-tune open-source LLMs using LoRA, RLHF, DPO, and model distillation techniques. * Implement model evaluation pipelines and benchmark reporting. * Collaborate with Prompt & Data teams to create ...
... techniques (RLHF, DPO, constitutional AI) - Experience with agentic AI systems, including planning, tool use, and orchestration - Experience with distributed training and large-scale model ...
... techniques (RLHF, DPO, constitutional AI) - Experience with agentic AI systems, including planning, tool use, and orchestration - Experience with distributed training and large-scale model ...
Develop RLHF and post‑training methods for multimodal models. * Build reward models and preference‑learning pipelines for adaptive, personalized model behavior. * Design datasets, rubrics, and ...
Develop RLHF and post‑training methods for multimodal models. * Build reward models and preference‑learning pipelines for adaptive, personalized model behavior. * Design datasets, rubrics, and ...
Flushing, NY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Flushing, NY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Manhattan, NY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
Manhattan, NY · On-site
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment ...
An RLHF (Reinforcement Learning with Human Feedback) job involves training AI models using human feedback to improve their responses. Professionals in this role analyze model outputs, provide evaluations, and refine AI behavior through reinforcement learning techniques. These roles are common in AI research, content moderation, and chatbot development.
| Aspect | Rlhf | Rn |
|---|---|---|
| Required Credentials | Licensed healthcare professional, often with specialized training in mental health or behavioral health | Licensed practical nurse or registered nurse, with nursing licensure and possibly additional certifications |
| Work Environment | Behavioral health facilities, clinics, hospitals, or community health settings | Hospitals, clinics, long-term care facilities, and community health settings |
| Employer & Industry Usage | Behavioral health and mental health services | General healthcare and nursing services |
| Common Search & Comparison | Rlhf vs Rn | Rlhf vs Rn |
While Rlhf (Registered Licensed Mental Health Facilitator) focuses on mental health support and behavioral health interventions, Rn (Registered Nurse) provides broader nursing care across various medical settings. Both roles require licensure, but Rlhf specializes in mental health, whereas Rn covers general patient care.
Cities with the most Rlhf job openings:
The most popular types of Rlhf jobs are:
States with the most job openings for Rlhf jobs include:
The top searched job categories for Rlhf jobs are:
San Francisco, CA • On-site
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This job post has expired today. Applications are no longer accepted.
Xterra is a Khosla Ventures-backed company building AI agents that reason about complex scientific problems. We’re not a wrapper around existing models, we’re training our own foundation models on top of large-scale proprietary datasets. This is a rare intersection of frontier AI and real-world scientific impact. Xterra is still in stealth mode.
The RoleWe’re looking for research scientists who want to work at the intersection of research and engineering, developing new methods for teaching AI systems to reason. You’ll own problems end-to-end, from idea through experimentation to production.
We’re hiring across multiple levels (early-career through senior/staff) and will calibrate scope and expectations to match your experience.
What You’ll Work On
