Rlhf Jobs (NOW HIRING)

Apply and refine evaluation rubrics for RLHF , SFT , and AI safety benchmarking . * Identify unsafe outputs, hallucinations, reasoning failures, and policy violations. * Provide structured feedback ...

Apply and refine evaluation rubrics for RLHF , SFT , and AI safety benchmarking . * Identify unsafe outputs, hallucinations, reasoning failures, and policy violations. * Provide structured feedback ...

Apply and refine evaluation rubrics for RLHF , SFT , and AI safety benchmarking . * Identify unsafe outputs, hallucinations, reasoning failures, and policy violations. * Provide structured feedback ...

Preferred : • Experience with RLHF or preference learning. • Experience with LLM agents or tool-using AI systems. • Multi-agent systems or long-horizon planning. • Simulation environments for ...

Required : • Hands-on experience with data generation and evaluation for LLM post-training • Experience training or fine-tuning models using SFT, instruction tuning, RLHF, DPO, or similar ...

Preferred : • Experience with RLHF or preference learning. • Experience with LLM agents or tool-using AI systems. • Multi-agent systems or long-horizon planning. • Simulation environments for ...

You'll be embedded directly with applied researchers and ML engineers running RLHF, fine-tuning, and preference-tuning pipelines, reading model outputs, calling out what's wrong, and turning that ...

Build, fine‑tune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows. * Develop APIs, data pipelines, and orchestration systems for multi‑agent ...

Responsibilities : • Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more. • Implement new methods in OpenAI's core model training and ...

Lead research spikes on emerging techniques (LLMs, multimodal, RLHF) to determine production viability. * Establish ML engineering best practices, including experimentation standards, model ...

Research Program Although RLHF and related methods, including direct preference optimization, are now widely used, their statistical properties remain only partially understood. Human feedback is ...

If you previously worked on post-training, RLHF, or trained models used by millions of people it's a big plus, but relevant experience is not required. * You take pride in your work and thrive in ...

Preferred : • Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and ...

Required : • Significant hands-on experience with RL, RLHF, RLAIF, post-training, alignment, or large-scale fine-tuning for modern foundation models. • Deep understanding of RL/post-training ...

RLHF, DPO, or equivalent • Experience designing evaluation frameworks for LLM or agentic systems • Strong proficiency in Python and PyTorch Preferred : • Background in Electrical or Computer ...

Preferred : • Experience with RLHF or preference learning. • Experience with LLM agents or tool-using AI systems. • Multi-agent systems or long-horizon planning. • Simulation environments for ...

LLM providers**, enterprises, and internal teams to design solutions that span **data labeling, annotation, localization, RLHF, and multi-modal workflows**. This is a leadership position requiring ...

... 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 ...

Help shape the post-training recipe-SFT, preference tuning (RLHF/DPO-style), distillation, and RL-and own key stages of how each turns a strong base model into a deployable policy. * Reasoning, Tool ...