We welcome exceptional people who share our vision and ambition.

Eluvio is a highly-focused and friendly team of system and application software engineers, data scientists, and security experts working together to implement the content fabric and bring it to the world of digital content. Our team is headquartered in Berkeley, CA, not far from UC Berkeley campus.

Our work extends the state-of-the-art in video engineering, Internet networking, data science and machine learning, blockchain security, and zero knowledge systems. We welcome highly skilled and creative individuals interested in full-time and internship opportunities across these domains. We not only innovate, we also work closely with the digital content community to validate our solutions and are looking for team members who are both visionary and practical!

Specific positions we are currently seeking are highlighted below. If you do not find a specific position that fits but believe you can uniquely contribute, please contact us at careers@eluv.io.

Current Positions

Senior Machine Learning Engineer / Data Scientist

Eluvio uses a wide range of machine learning and deep learning techniques within its content fabric.

This position offers an experienced scientist/engineer an opportunity for big impact, working in a small, excellent team innovating new ML, DL and data science solutions.

Responsibilities

Build production level machine learning models on large-scale datasets to increase the intelligence of video/audio content

Optimize content routing, re-use, transformation and delivery algorithms

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

Desired Qualifications

Master's Degree or PhD in Computer Science & Engineering/Statistics/Math/Physics

Minimum of 1-3 years of working experience as a data scientist or machine learning engineer

Expertise with Python or R

Experience with machine/deep learning algorithms (e.g. gradient boosting, CNNs, sequence models) and frameworks/libraries (e.g. Tensorflow, PyTorch, Scikit-learn)

Advanced SQL skills, comfortable working with very large data sets

Previous experience in computer vision and natural language processing (e.g. object detection, video/image/text classification, image captioning, image-to-image translation) is a plus

Great communication skills, organized, able to multitask and be a team player

Ability to balance attention to detail with agile execution

Summer Intern, Machine Learning / Data Science

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 within our software engineering team on ML, DL and data science solutions.

Responsibilities

Work with the Eluvio Machine Learning and Data Science Team to:

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

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, scikit-learn)

Knowledge of computer vision and natural language processing

Great communication skills, organized, able to multitask and be a team player

Ability to balance attention to detail with agile execution