ML Researcher - Posttraining

📋 Description

• Finetune diffusion models at scale to improve image aesthetics and quality.
• Implement posttraining techniques ranging from supervised finetuning, preference optimization
• Design comprehensive eval suites and reward designs for the reinforcement learning stage focused on
• Train custom VLM as reward models as part of our reward design.
• Train custom LLMs for prompt expansion through finetuning and reinforcement learning.
• Coordinate with data teams and partners to manage collection of preference data and model

🎯 Requirements

• Proven work of posttraining diffusion models for image or video generation.
• Experience with large-scale model training, inference, and optimization.
• Strong understanding of both LLM and diffusion post training pipelines and algorithms such as PPO
• Strong proficiency in PyTorch and understanding of its inner workings.
• Strong background in distributed training paradigms such as FSDP, CP, SP, USP, TP, and EP. Knowing
• Good knowledge of low precision training / inference in FP8, NVFP4, and MXFP8.

🎁 Benefits

• Competitive compensation: generous salary & equity packages
• Health & wellness: 100% health & 99% dental/vision insurance premiums covered for
• Time off: Flexible PTO policy
• Financial planning: 401k with a 4% company-sponsored match
• Meals in the office: breakfast, lunch, dinner - you name it, we'll cover it
• Transit: Ubers covered to & from the office