RLHF Specialist

About the role

The RLHF Specialist will design and operate feedback pipelines that improve large language models through Reinforcement Learning from Human Feedback. Working remotely, you will collaborate with ML engineers to align model behavior with safety, factual accuracy, and human values.

Key responsibilities

• Generate high‑quality preference data by ranking model responses on helpfulness, honesty, and harmlessness.
• Craft multi‑turn prompts to stress‑test reasoning and safety, and write chain‑of‑thought explanations for reward‑model training.
• Partner with engineers to analyse failure modes, identify data gaps, and propose targeted data interventions.
• Develop and maintain annotation guidelines, ensuring consistency across a global team.
• Probe models for biases, hallucinations, or reward‑hacking patterns and document findings.
• Maintain a personal benchmark set to monitor model performance over time.

Required profile

• At least 2 years of experience in data annotation, model evaluation, computational linguistics, or AI safety.
• Strong understanding of reinforcement‑learning concepts such as PPO, trust‑region methods, and reward hacking.
• Proven ability to fine‑tune open‑source LLMs and diagnose RL policy issues.

Required skills

• Python programming.
• Deep‑learning frameworks: PyTorch, JAX, TensorFlow.
• Fine‑tuning techniques: LoRA, QLoRA.
• Experience with LLMs (Llama 2/3, Mistral, Gemma).
• Annotation platforms: LabelBox, Scale AI, Snorkel.
• Cloud services: AWS SageMaker, GCP Vertex AI.