# Research Scientist Intern - VLM and Omni Model Post-Training at Meta

- Company: [Meta](https://meta.com)
- Location: Sunnyvale, CA
- Type: Internship · Internship
- Posted: 2026-10-13
- Apply: https://www.metacareers.com/jobs/2988199118196184
- Page: https://newgrad.ai/jobs/research-scientist-intern-vlm-and-omni-model-post-training-7084a49e

## Summary by newgrad.ai

What you'll do:

- Create reinforcement learning methods for multimodal reasoning and decision-making.
- Design reward models to improve temporal grounding and model calibration.
- Develop algorithms for post-training vision-language and omni models.
- Build evaluation frameworks to identify reward hacking and model failures.

What they're looking for:

- Availability for a 12 to 24-week internship duration.
- Interest in streaming video, speech, and audio-based model training.
- Ability to combine supervised fine-tuning with preference learning techniques.

## Posting

The Meta Reality Labs Research Team brings together researchers, developers, and engineers to create the future of AR, VR, and contextual AI. The Surreal Vision group at Reality Labs Research is seeking outstanding Research Scientist Interns to advance posttraining of vision-language and omni models. As an intern, you will develop reinforcement learning (RL) methods that improve multimodal reasoning, temporal understanding, and grounded decision-making. Applications include procedural and real-time task assistants for future contextual AI devices.

### Your research project may cover or relate to the following topics:

- Developing RL posttraining algorithms for VLMs and omni models, including on-policy optimization and learning from expert feedback.
- Designing reward models and verifiable rewards for multimodal reasoning, temporal grounding, and calibrated decisions.
- Combining supervised fine-tuning, preference learning, and RL to improve data efficiency, training stability, and generalization.
- Posttraining with streaming video, speech, and environmental audio to improve reasoning.
- Building evaluations and ablations that measure grounded model improvements and identify reward hacking and failures under ambiguous evidence.

Our internships are twelve (12) to twenty-four (24) weeks long and we have flexible start dates.

From Meta's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.

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More new-grad and intern roles: https://newgrad.ai/llms.txt