Machine Learning Intern
Conduct research and engineering on next-generation video generation models, including post-training, evaluation, multimodal data systems, and scalable ML infrastructure. The internship requires current bachelor's or master's study and practical experience with Python, data pipelines, or distributed systems.
About the job
Responsibilities
- Develop reward models to improve aesthetics, motion quality, temporal consistency, and prompt adherence in video generation models.
- Study base-model behavior and use experimental findings to inform model development.
- 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 recurring dataset refreshes.
- Improve the reliability, reproducibility, and efficiency of data and model-training workflows.
- Build tooling for video and multimodal data using FFmpeg, PyAV, DALI, OpenCV, or equivalent technologies.
- Contribute to evaluation harnesses, model integrations, research tooling, and related product-adjacent projects.
- Document and communicate findings through research reports, presentations, demonstrations, and potential conference submissions.
Requirements
- 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 work, or 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 and interest in building reliable systems for large-scale machine learning.
Nice to Have
- Experience with video, image, audio, or other multimodal data.
- Publications at venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or AAAI.
Compensation and Benefits
- Competitive monthly stipend.
- Visa and travel support for eligible international candidates.
- Housing support for qualifying international interns in Singapore.
- Defined project, named senior mentor, weekly one-on-one meetings, and project milestones.
- Compute allocation, equipment, and resources for research.
- Conference travel support for accepted papers.
- Three-month onsite internship with batches starting in October 2026 and January 2027.
Skills
Python, Ray, Pyspark, Airflow, Docker, Kubernetes, AWS, GCP, Azure, Ffmpeg, Pyav, Dali, Opencv, Distributed Systems, ML Infrastructure
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