Machine Learning Intern

Cantina Labs is a social AI company developing a suite of advanced video generation models. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.

About the Internship

Cantina is growing its research lab in Singapore, and we are looking for exceptional machine learning interns to work with us on the next generation of video models in October 2026.

What You’ll Work On

Develop reward models to improve aesthetics, motion quality, temporal consistency, and prompt adherence

Study how base-model behavior affects post-training outcomes and use experimental findings to inform model development

Design rigorous evaluations and conduct large-scale experiments on generative video models

Build systems for ingesting, preprocessing, curating, and delivering large-scale video datasets

Develop distributed pipelines for dataset generation, deduplication, preprocessing, and repeated dataset refreshes

Improve the reliability, reproducibility, and efficiency of data and model-training workflows

Build tooling for video and multimodal data using technologies such as FFmpeg, PyAV, DALI, or OpenCV

Contribute to evaluation harnesses, model integrations, research tooling, or other product-adjacent projects related to your core work

Document and communicate your findings through research reports, internal presentations, demonstrations, and potential conference submissions

You may be a good fit if you

Are pursuing a bachelor’s or master’s degree in computer science, engineering, machine learning, or a related field

Have experience building data pipelines, ML infrastructure, or distributed systems through research, coursework, open-source contributions, or previous internships

Are familiar with tools such as Ray, PySpark, Airflow, Docker, Kubernetes, or equivalent technologies

Have worked with cloud storage or compute platforms such as AWS, Google Cloud, or Azure

Understand practical considerations around data throughput, storage layout, caching, monitoring, and failure recovery

Are proficient in Python and interested in building reliable systems for large-scale machine learning

Experience with video, image, audio, or other multimodal data is valuable. Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or AAAI are a plus, but are not required. We care most about the quality of your thinking, the depth of your technical work, and your ability to learn quickly.

What You Can Expect

A defined project and named senior mentor before your first day

Weekly one-on-one meetings and clear project milestones

A meaningful compute allocation for your research

The opportunity to own a complete research or engineering result

First-author positioning by default where your contribution supports a publication

Timely internal review of research intended for submission

Support for conference travel if your paper is accepted

Opportunities to demonstrate your work and receive credit for product contributions

A competitive monthly stipend

Visa and travel support for eligible international candidates

Housing support for qualifying international interns in Singapore

Equipment and resources needed to complete your work

Duration: Three months

Working model: Onsite

Start dates: Start dates: First batch starts in October 2026; second batch starts in January 2027

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