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 enhance model safety, factual accuracy, and alignment with human values.

Key responsibilities

• Generate high‑quality preference data by ranking model responses on helpfulness, honesty, and harmlessness.
• Design multi‑turn prompts to stress‑test reasoning and safety, and write chain‑of‑thought rationales for reward‑model training.
• Collaborate with engineers to analyse failure modes, identify data gaps, and propose data‑driven interventions.
• Develop and iterate annotation strategies, ensuring consistency across a global team.
• Probe models for biases, hallucinations, and vulnerabilities, documenting findings for optimisation.
• Maintain a personal benchmark set to monitor performance across model versions.

Required profile

• Minimum 2 years experience in data annotation, model evaluation, computational linguistics, or AI trust & safety.
• Strong understanding of reinforcement‑learning concepts (PPO, trust regions, reward hacking) applied to language generation.
• Hands‑on experience fine‑tuning open‑source models (e.g., Llama 2/3, Mistral, Gemma) with LoRA/QLoRA.
• Experience with human‑in‑the‑loop workflows and annotation platforms.

Required skills

• Python
• PyTorch
• JAX
• TensorFlow
• LoRA / QLoRA
• LabelBox
• Scale AI
• Snorkel
• AWS SageMaker
• GCP Vertex AI