Research Engineer – Post-Training (AI)

About the role

Join the Post-Training team as a Research Engineer and work on fine‑tuning large language models, improving their performance, and ensuring high quality and efficiency. Your contributions will directly impact millions of daily user interactions and help shape the future of consumer AI.

Key responsibilities

• Develop alignment algorithms and loss functions to improve data sample efficiency.
• Write data pipelines that transform diverse web data into model‑ready formats.
• Identify quality signals to evaluate model performance in real‑world settings.
• Design sampling algorithms that boost serving efficiency of large generative models.

Required profile

• PhD (or equivalent) in a relevant field.
• Proven ability to write clean, production‑ready training code.
• Experience working with GPUs for training, serving, and debugging.
• Strong background in modern machine‑learning techniques such as reinforcement learning and transformers.
• Track record of exceptional research or applied ML projects.

Required skills

• GPUs for deep‑learning workloads.
• Data pipeline development.
• Reinforcement learning.
• Transformers.
• Kubernetes and Docker for ML deployment.
• Cloud computing platforms.
• Distributed training of large models.