About Us

We at Eluvio (https://eluv.io) are solving the generational problems of video over the Internet. The Content Fabric is a next-generation content distribution and storage protocol deployed in a global network of nodes transforming the distribution and monetization of premium video and digital media-in contrast to legacy cloud workflows and CDNs. The Fabric provides a new and innovative decentralized video processing framework with the ambition of serving a sizable percentage of the world's Internet video with just-in-time and personalized experiences.

Components are real-time content routing, just-in-time code execution on ingress and egress, an inline frame-accurate video and content AI stack, and blockchain-controlled content encryption, verification and authorization. Our users are innovative sports and entertainment brands -- Amazon Studios/MGM, Cricket Australia, European Professional Club Rugby, NBA, Red Bull, SONY, UEFA, United Rugby Championship, Warner Bros., and WWE, to name a few. We aim to serve all content owners who distribute and harness video and other valuable content IP. On X: @EluvioInc; On LinkedIn: Eluvio https://www.linkedin.com/company/eluv-io/.

Our Team

Our team is a highly focused and ambitious team of software engineers and computer scientists in systems, networking, applications, and video; AI and ML, and security/cryptography working together to implement the vision of the Content Fabric. We build with a first-principles approach, and have been recognized with many innovation and product awards such as NAB Streaming Product of the Year (2024 and 2025), the SEICON Grand Prize, and the HPA Engineering Excellence Award, and we hold 15 issued US patents. We are led by founders Michelle Munson and Serban Simu, who previously built and sold Aspera, an Emmy award winning technology and major acquisition by IBM. The team includes several other leaders who have built companies with successful exits. Our HQ is in Berkeley, CA, not far from the UC Berkeley campus and we were part of the UC Berkeley Blockchain Xclerator.

The Role

This role is focused on Outstanding New Graduates who wish to join our team as a full-time Software Engineer.

Candidates should have an outstanding academic background and demonstrated excellent foundational knowledge, and a deep appetite to learn and contribute. BSc is the minimum, MSc and PhD welcome. We will steer you toward our Core, Applications or AI/ML teams based on your fit.

In the Core, backend work is based on Go, Rust and C, including native and Web Assembly binaries and includes a full video/audio transcoding, packaging, and processing stack, in addition to the decentralized content routing/storage protocol.

Our Apps and Front-end are largely JavaScript (browser), native TV and Mobile apps (iOS/Android, and others) and Web Assembly, and span a wide range of content streaming, download, and viewing experiences.

Our AI/ML team builds, trains, and applies large and small models across varied applications in content description, summarization, search, retrieval and personalization utilizing LLMs/VLMs/RAG, reinforcement learning, statistical and ML optimization, and data science.

Our main offices are located in Berkeley, CA but, for the right candidate and circumstances remote work is possible.

Requirements

Minimum BSc in EECS or a related discipline (MSc or PhD is great!)
Demonstrated excellence in classroom, internship, or open source software and model development.
Excellent understanding of core computer science fundamentals in chosen focus areas such as algorithms, concurrent programming, security, networking, and machine learning. Research and development experience in new problem areas preferred
For Core - Working knowledge of a low level programming such as Go, Rust, or C/C++, including unit and integration tests, and strong versatility working up and down the stack
For Apps - Working knowledge of JavaScript, full-stack application development, and current MVC/react or equivalent frameworks, including ability to write modular and testable code. Knowledge of mobile/TV native code, e.g. iOS, tvOS, Android, AndroidTV a plus
For ML/AI - Deep classroom experience in data science or machine learning or internship; Comfortable with Python. Knowledge of machine/deep learning algorithms - the more the better (e.g. RAG, encoding/decoding Transformers, LLM/LVLM fine-tuning, gradient boosting, CNNs, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Sci kit-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
Ability to think creatively and innovate new solutions to hard problems

Nice to Have

For core - Applied cryptography, including SECP256-based protocols, proxy re-encryption, threshold ciphers and protocols. Familiarity and experience with H.264, H.265, AV-1 standards and generally codec standards. Familiarity and experience with WebRTC. Full-stack application experience operating and using video tools such as ffmpeg Understanding and familiarity with java-script based media players
For AI/ML - Extended experience creating new fine-tuned and multi-stage AI/ML pipelines including latest R&D in LLVMs/Mix-of-experts/LoRA/Advanced Optimization/Advanced RAG and statistical techniques

Benefits

A chance to be part of a technology that is literally changing the world of Video and Content on the Internet, working with and learning from some the best engineers in the world, and a chance to make your mark
Market competitive salary
Employee stock option program
Medical, Dental, Vision, 401K
Work Hard / Play Hard - we celebrate our accomplishments with at least 2 parties a year, and we have a warm and casual working environment. Lunch is provided every day
Conferences, tech events, and customer interaction are common. We publish in our field, give talks, present at product conferences and interface with our customers regularly. You can take part!

Eluvio

Latest Jobs

Software Engineer New Grad (MSc/BSc: AI, Core, Apps)