LLM Post-training Engineer Intern (Research & Product) - 2027 Summer

• Support the development and optimization of post-training strategies, including instruction tuning, preference tuning (SFT/DPO/PPO), and model alignment.
• Assist in building robust evaluation pipelines to measure model performance, helpfulness, and safety across diverse multimedia product use cases.
• Participate in the research and implementation of cutting-edge methodologies in reward modeling and human preference learning.
• Collaborate with engineering teams to bridge the gap between experimental research and production-ready AI applications (e.g., video understanding, translation, and content classification).
• Analyze and process large-scale datasets to identify patterns that improve model behavior and alignment quality.

• Currently pursuing an Undergraduate or Master’s degree in Computer Science, Machine Learning, or a related technical discipline.
• Strong programming skills in Python and experience with deep learning frameworks such as PyTorch or JAX.
• Foundational understanding of Transformer architectures and LLM training principles.
• Demonstrated ability to learn quickly in a fast-paced environment and a strong passion for AI "landing" and product application.

• Previous experience or research projects involving LLM fine-tuning, RLHF, or synthetic data generation.
• Familiarity with distributed training tools (e.g., DeepSpeed, Megatron-LM).
• Experience or interest in multimodal AI (integrating text with video or audio).
• Proven track record of building and deploying AI projects, either through previous internships, open-source contributions, or academic research.

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