Machine Learning Intern

Speedrun Talent Network

Singapore

Hybrid

SGD 28,000 - 42,000

Full time

14 days+

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Benefits offered by this job

Visa support

Housing assistance for international

Job summary

Cantina Labs is seeking exceptional machine learning interns to work on the next generation of video models in Singapore for a three-month onsite internship starting October 2026. You will be matched to a project and work closely with a senior mentor from problem formulation through experimentation, evaluation, and potential conference submission.

You’ll gain hands-on experience with data pipelines, model training, and evaluation tooling, using Python, FFmpeg, PyAV, and OpenCV, with a

Qualifications

Pursuing a bachelor’s or master’s degree in computer science, engineering, ML, or related field.
Experience building data pipelines, ML infrastructure, or distributed systems through research, coursework, open-source contributions, or previous internships.
Familiar with tools such as Ray, PySpark, Airflow, Docker, Kubernetes, or equivalent technologies.
Proficient in Python and building reliable systems for large-scale ML.

Responsibilities

Develop reward models to improve aesthetics, motion quality, temporal consistency, and prompt adherence.
Study base-model behavior and use 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 refreshed datasets.
Improve reliability, reproducibility, and efficiency of data and model-training workflows.
Build tooling for video and multimodal data using FFmpeg, PyAV, DALI, or OpenCV.
Contribute to evaluation harnesses, model integrations, research tooling, or product-adjacent projects.

Skills

Python

Data pipelines

ML infrastructure

Distributed systems

Education

Bachelor's or Master's in CS/Engineering/ML

Tools

Ray

PySpark

Airflow

Docker

Kubernetes

Job description

About Cantina

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.

This is a three month onsite internship designed to give you meaningful ownership of a well-defined research or engineering problem. You will be matched with a project based on your background and interests, working closely with a senior mentor from initial problem formulation through experimentation, evaluation, and, where appropriate, submission to a leading AI conference.

Projects may focus on post-training and inference efficiency for video generation models, reward modeling and preference-based optimization, multimodal data systems, or scalable infrastructure for video model training. The primary focus will be your core project, with opportunities to contribute to applied or product-adjacent work where relevant.

What You’ll Work On

Depending on your project, you may:

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