Machine Learning Engineer Intern

2 weeks ago


Aarhus, Denmark Roku Full time

Teamwork makes the stream work.

Roku is changing how the world watches TV

Roku is the #1 TV streaming platform in the US, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.

From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.

About the team

Roku pioneered in developing operating system for TVs. Tv Technology team within Roku TV NPI group is focused on building TVs with best Audio Quality , Picture Quality and Enable innovation technology. With tens of million TVs sold across many countries, thousands of streaming channels and billions of hours watched over the Roku TVs, having best Audio Quality & Picture Quality is crucial.

About the role

This role is for a Summer 2024 Internship and will eventually be based in Aarhus , Denmark
We are looking for a creative and passionate Machine Learning (ML) / Deep Learning (DL) Intern to join Roku TV team. You will be tasked to explore Audio Quality (AQ) improvements using AI in a resource constraint environment. Roku is pushing the limits in all directions, and AQ is one of these.

What you’ll be doing

working in ML model development training data set collection for Audio quality enhancement

We’re excited if you have/are

Currently pursuing your Masters/PhD in Computer Science, Electrical Engineering or related fields Research background is preferred. Should be able to understand and implement technical papers on ML/DL Bonus to have published paper(s) in the field of ML/DL Hands-on Machine Learning / Deep Learning and TensorFlow/PyTorch Have experience in coding ML/DL algorithms in Python Bonus if familiar with Audio pipeline Excellent communication skills, and solid work ethic Affinity to Language models and processing

#LI-JH1

Benefits

Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Our employees can take time off work for vacation and other personal reasons to balance their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.

The Roku Culture

Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We’re independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV. 

We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002. 



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