Machine Learning Intern

Cantina

. Work on the next generation of video models with a senior mentor .

Posted 10/27/2026internshipSingapore • SingaporeEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing video models and data pipelines, with a strong foundation in machine learning and distributed systems. Proficient in Python and familiar with cloud platforms and video processing tools to enhance model performance and data handling.

Highest-signal resume keywords

Python ProficiencyData Pipeline DevelopmentDistributed Systems ExperienceFamiliarity With Cloud PlatformsVideo Processing Tools Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Pipeline DevelopmentModel EvaluationVideo Model DevelopmentDistributed SystemsData PreprocessingMultimodal Data HandlingExperimental DesignData Throughput UnderstandingModel Training Workflows

Soft Skills

CommunicationDocumentationCollaboration

Tools & Technologies

FFmpegPyAVDALIOpenCVRayPySparkAirflowDockerKubernetesAWS

Industry Keywords

Generative Video ModelsLarge-Scale ExperimentsResearch ToolingModel IntegrationsPublications in NeurIPSICMLICLRCVPRICCVECCV

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDistributed SystemsDockerFFmpegKubernetesPySparkPythonRay

About the role

Key responsibilities & impact

Work on the next generation of video models with a senior mentor
Develop reward models to improve aesthetics, motion quality, temporal consistency, and prompt adherence
Study base-model behavior and inform model development through experimental findings
Design 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 reliability, reproducibility, and efficiency of data and model-training workflows
Build video and multimodal data tooling using FFmpeg, PyAV, DALI, or OpenCV
Contribute to evaluation harnesses, model integrations, research tooling, and product-adjacent projects
Document and communicate findings through research reports, internal presentations, demonstrations, and potential conference submissions

Requirements

What you’ll need

Are pursuing a bachelor’s or master’s degree in computer science, engineering, machine learning, or a related field
Experience building data pipelines, ML infrastructure, or distributed systems through research, coursework, open-source contributions, or previous internships
Familiarity with Ray, PySpark, Airflow, Docker, Kubernetes, or equivalent technologies
Experience with cloud storage or compute platforms such as AWS, Google Cloud, or Azure
Understanding of data throughput, storage layout, caching, monitoring, and failure recovery
Proficiency in Python
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

Benefits

Comp & perks

A meaningful compute allocation for your research
First-author positioning by default where your contribution supports a publication
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
Defined project and named senior mentor before your first day
Weekly one-on-one meetings and clear project milestones