Research Scientist; post-training

# Research Scientist (post-training)
Genmo San Francisco HQFull-timeAI tools:

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You’ll research alignment and post-training methods for Genmo’s video-generation models, including supervised fine-tuning and reinforcement learning from human feedback. The work spans evaluation, feedback-data pipelines, and integrating improvements into production alongside research and product teams.
* Permanent* On-site
* PhD required
* PhD### Skills and expertise

Py Torch Reinforcement  learningRLHFSupervised fine-tuning

Diffusion models

Distributed training

Model evaluation

Human feedback data pipelines### Key responsibilities
* Lead research on alignment and post-training methods for video-generation models.
* Build fine-tuning, RLHF, evaluation, and human-feedback pipelines.
* Run experiments and integrate alignment improvements into production with cross-functional teams.## How this job compares

Compared with 90 open mid-level research jobs on October 10, 2026.Pay:
This job does not publish its pay. The 32 open mid-level research jobs that publish US pay start at $199K a year on average.

Similar open jobs:
We Love AI Jobs lists 90 open mid-level research jobs at 53 companies.

Remote work:
This job is on site. 12 of the 90 mid-level research jobs (13%) are remote.

AI in this role:
High. AI is the core of the work: building, training or deploying AI systems. The role centers on training, evaluating, and aligning large-scale video-generation models. It includes implementing RLHF pipelines and integrating model improvements into production.## Full description

We are Genmo, a research lab developing the world’s most sophisticated video world models to understand, simulate, and interact with the physical world. Our mission is to unlock the right brain of AGI. Join us in advancing physical intelligence and enabling robots to learn and act in a changing world.

Role overview:

We are seeking an exceptional Research Scientist to join our team, focusing on alignment and post-training techniques for large-scale video generation models. In this role, you will be at the forefront of ensuring our diffusion-based video models reliably produce high-quality, physically accurate and safe outputs that match human preferences and values.

Key responsibilities:

• Lead research initiatives in alignment and post-training methods for video generation models, focusing on improved quality, reliability, and adherence to human intent
• Design and implement supervised fine-tuning and reinforcement learning from human feedback (RLHF) pipelines for video generation models
• Develop robust evaluation frameworks to measure model alignment, safety, and output quality
• Create and optimize data collection pipelines for human feedback and preferences
• Design and conduct experiments to validate alignment techniques and their scaling properties
• Collaborate with cross-functional teams to integrate alignment improvements into our production pipeline
• Stay at the cutting edge of the field by regularly reviewing academic literature in both generative AI and alignment
• Mentor junior researchers and foster a culture of responsible AI development
• Work closely with product teams to ensure alignment methods enhance rather than inhibit model capabilities

Qualifications:

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field
• Must have:
• Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR) with a focus on reinforcement learning, alignment, or generative models
• Extensive experience implementing and optimizing large-scale training pipelines using Py Torch
• Deep understanding of reinforcement…