E

Last Minute AI-Machine Learning Summer Internship (Gen AI - Multimodal)

icon building Company : Eluvio
icon briefcase Job Type : Internship

Number of Applicants

 : 

000+

Click to reveal the number of candidates who applied for this job.
icon loader
Apply Now
icon loader Apply Now

Let AI Supercharge Your Job Hunt!

JobCopilot scans 500,000+ company career sites daily to find jobs for you

Never miss an opportunity Save hours by auto-filling applications forms Land more interviews with tailored applications
happy man
thunder iconActivate JobCopilot

Job Description - Last Minute AI-Machine Learning Summer Internship (Gen AI - Multimodal)

Description

If you are an outstanding upper undergrad, recent grad or grad student and are looking for an amazing last-minute Summer Internship - this is the opportunity for you! Eluvio AI is growing fast and we have a new internship position available in our Berkeley HQ!

Eluvio is a highly focused and ambitious team of systems, networking, application, and video software engineers, AI scientists, ML engineers, and security experts working together to implement the vision of the Content Fabric - a decentralized platform for video and commerce with the ambition of serving the world's Internet video. The Eluvio Content Fabric provides an innovative distributed and decentralized video processing framework with just-in-time and personalized experiences, made possible through our state-of-the-art real-time content routing and just-in-time code execution. We are headquartered in Berkeley, CA. 

Eluvio uses a wide range of machine learning and deep learning techniques within its content fabric. This position offers an internship opportunity for students with excellent academic records pursuing graduate degrees in computer science, data science, or related fields (or advanced undergraduates) to work in our office with our software engineering team on ML, DL and data science solutions.

Responsibilities

  • Work with the Eluvio AI Machine Learning and Data Science Team
  • Build production level machine learning models on large-scale datasets to increase the intelligence of video/audio content
  • Provide data-driven recommendations and actionable insights on problems such as content understanding/augmentation/location
  • Develop multi-functional learning pipelines
  • Collaborate with product and engineering teams to implement models at scale
  • Help train and develop multimodal learning models using advanced learning techniques including RAG, self-supervised learning, semi-supervised, and transductive learning.


Requirements

Desired Qualifications

  • MSc or PhD student in Computer Science & Engineering/Statistics/Math/Physics, or Advanced Undergraduate
  • Deep classroom experience in data science or machine learning or prior internship
  • Comfortable with Python or R
  • Knowledge of machine/deep learning algorithms (e.g. gradient boosting, CNNs, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Sci kit-learn)
  • Knowledge of computer vision and natural language processing
  • Strong working experience with large multi-modal and language models preferred
  • Great communication skills, organized, able to multitask and be a team player
  • Ability to balance attention to detail with agile execution


Benefits

Paid summer internship with one of the top Video AI tech companies in the world!

Catered Lunches (really good food)

Great atmosphere, nice colleagues

Summer Party!

Original job Last Minute AI-Machine Learning Summer Internship (Gen AI - Multimodal) posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
Apply Now
Share Job
Share Job

Auto-Apply to Machine Learning Internship Jobs with your AI JobCopilot

thunder icon Auto-Apply with AI

Similar Machine Learning Internship Jobs in the US

GrabJobs is the no1 job portal in the US, connecting you to thousands of jobs fast! Find the best jobs in the US, apply in 1 click and get a job today!

Mobile Apps

Copyright © 2026 Grabjobs Pte.Ltd. All Rights Reserved.