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

Eluvio•Berkeley, CA

4d•Onsite

About The Position

Eluvio AI is seeking an outstanding upper undergraduate, recent graduate, or graduate student for a last-minute Summer Internship. Eluvio is a fast-growing company with a highly focused and ambitious team of systems, networking, application, and video software engineers, AI scientists, ML engineers, and security experts. They are working together to implement the vision of the Content Fabric, a decentralized platform for video and commerce designed to serve the world's Internet video. The Eluvio Content Fabric offers an innovative distributed and decentralized video processing framework with just-in-time and personalized experiences, enabled by state-of-the-art real-time content routing and just-in-time code execution. Eluvio utilizes a wide range of machine learning and deep learning techniques within its content fabric. This internship offers an opportunity for students with excellent academic records pursuing graduate degrees in computer science, data science, or related fields (or advanced undergraduates) to work in the Berkeley, CA office with the software engineering team on ML, DL, and data science solutions.

Requirements

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

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.