Logo for Reality Defender

Multimodal AI PhD Intern (Spring 2026)

Roles & Responsibilities

  • PhD student in a relevant technical field, preferably three or more years into the program.
  • Experience in multi-modal learning, such as audio-visual classification and audio-language reasoning.
  • Proficient in Python and building deep learning models with PyTorch.
  • Published peer-reviewed research papers in reputable AI and speech venues (e.g., CVPR, NeurIPS, ACL, Interspeech).

Requirements:

  • Investigate and propose new methods for detecting generative multi-modal content spanning audio and vision modalities.
  • Perform research on multi-modal deepfake detection and reasoning tasks.
  • Collaborate with researchers on the team and write up results of research for internal reports and submissions to academic journals/workshops.
  • Independently implement and evaluate ideas on the modern deep learning stack (Python, PyTorch) and GPU-enabled cloud compute (e.g., AWS/GCP).

Job description

Who we are.

Reality Defender is an award-winning cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media. Utilizing a patented multi-model approach, Reality Defender is robust against the bleeding edge of generative platforms producing video, audio, imagery, and text media. Reality Defender's API-first deepfake detection platform empowers teams and developers alike to identify fraud, disinformation campaigns, and harmful deepfakes in real time.

Backed by world class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender works with leading enterprise clients, financial institutions, and governments in order to ensure AI-generated media is not used for malicious purposes.

Youtube: Reality Defender Wins RSA Most Innovative Startup

The Multimodal AI Internship.

The 4-month internship is designed for current PhD students and candidates to partner with Reality Defender's AI team to conduct cutting-edge research and publish peer-reviewed papers. Your primary collaborators will be Surya Koppisetti and Yi Zhu, who will guide and advise your efforts within multi-modal deepfake detection. This internship can be performed remotely, although you're welcome to work from our HQ in New York City.

What you'll do.

  • Investigate and propose new methods for detecting generative multi-modal content, spanning audio and vision modalities.

  • Perform research on multi-modal deepfake detection and reasoning tasks.

  • Collaborate with researchers in the team.

  • Write up results of research for internal reports and submission to academic journals/workshops.

  • Independently implement and evaluate ideas on modern deep learning stack - Python, PyTorch, and GPU-enabled cloud compute, like AWS/GCP.

Who you are.

  • PhD student in a relevant technical field, preferably three or more years into the program

  • Experience in multi-modal learning, such as in audio-visual classification and audio-language reasoning.

  • Proficient in Python and in building deep learning models with PyTorch.

  • Published peer-reviewed research papers in reputable AI and speech venues, e.g. CVPR, NeurIPS, ACL, Interspeech.

  • Excited about Reality Defender's mission to build a best-in-class and comprehensive deepfake and AI-generated content detection platform.

  • Available to start in Spring 2026, for a minimum duration of 4 months.

AI Specialist Related jobs

We help you get seen. Not ignored.

We help you get seen faster — by the right people.

🚀

Auto-Apply

We apply for you — automatically and instantly.

Save time, skip forms, and stay on top of every opportunity. Because you can't get seen if you're not in the race.

✨

AI Match Feedback

Know your real match before you apply.

Get a detailed AI assessment of your profile against each job posting. Because getting seen starts with passing the filters.

Upgrade to Premium. Apply smarter and get noticed.

Upgrade to Premium

Join thousands of professionals who got noticed and hired faster.