Research Scientist (post-training)

We Love AI Jobs; San Francisco (CA); On-site; USD 190,000 - 260,000; Full time

Job summary

Genmo in San Francisco is seeking an exceptional Research Scientist to advance alignment and post-training techniques for our diffusion-based video generation models. You will lead experiments, design RLHF and supervised fine-tuning pipelines, and collaborate with research and product teams to improve reliability and safety.

The role emphasizes rigorous evaluation, data-collection for human preferences, and close integration of research with production.

Qualifications

• PhD in CS/AI/ML or related field.
• Strong publication record in NeurIPS/ICML/ICLR.
• Experience building large-scale training pipelines with PyTorch.
• Experience with RLHF and distributed training.
• Excellent communication and software engineering skills.

Responsibilities

• Lead research initiatives in alignment and post-training methods for video generation models.
• 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 scaling properties.
• Collaborate with cross-functional teams to integrate alignment improvements into production.
• Stay at the cutting edge by reviewing academic literature; mentor junior researchers.

Skills

PyTorch

Reinforcement learning

RLHF

Supervised fine-tuning

Diffusion models

Distributed training

Model evaluation

Human feedback data pipelines

Education

Ph.D. in Computer Science, AI, ML, or related field

Job description

# Research Scientist (post-training)GenmoSan Francisco HQFull-timeAI tools:PyTorchUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageYou’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 expertisePyTorchReinforcement learningRLHFSupervised fine-tuningDiffusion modelsDistributed trainingModel evaluationHuman 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 comparesCompared 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 descriptionWe 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 capabilitiesQualifications:• 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 PyTorch• Deep understanding of reinforcement learning techniques, particularly RLHF• Experience with distributed training systems and large-scale experiments• Proven track record in designing and implementing robust evaluation frameworks• Excellent communication skills with the ability to explain complex technical concepts to diverse audiences• Strong software engineering skills and experience with complex shared codebases• Ideal candidate will have:• Experience with diffusion models or other generative architectures• Background in fine-tuning large language models or generative models• Experience working with human feedback data collection and annotation pipelines• Strong aesthetic sense and understanding of video quality assessment• Familiarity with alignment techniques such as constitutional AI or debate• Track record of successful collaboration with product teams• Experience with perceptual quality metrics and human evaluation design• Contributions to open-source projects in AI alignment or generative AIAdditional InformationThe role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation.Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.