Careers

THE  CHALLENGE

Our main focus at the moment is video streaming: we are building models that can understand a video, where it makes the most sense to insert advertising, then insert it realistically. As opposed to most applied DL problems, this is a visual task which humans are naturally good at but has yet. We’ve broken down the technical requirements into individual steps which are more achievable such as intrinsic image decomposition, object tracking and surface normal estimation.

ABOUT THE ROLE

Computer Vision is at the core of the solutions that Sticheo provides. Our Computer Vision Engineers will at the same time use the latest technologies in a variety of real world scenarios, but also push the boundaries of what is being done in the field.

RESPONSIBILITIES

• Design, implement creative research solutions to big problems with the possibility to have a significant commercial impact
• Adapt the latest developments in research to work in real-world settings
• Identify and prioritise research directions and adapt research processes as the company expands
• Advocate and guide strategy for design and product direction
• Mentor and advise researchers

REQUIREMENTS

• PhD in Computer Vision, Deep Learning or related disciplines from a top research university
• Strong publishing track record (ICLR, ICML, NIPS, ICCV, etc) and proven ability to independently produce new research ideas
• 2+ years of experience using deep learning
• Proven ability to write production-quality research code
• Experience using deep learning frameworks (Tensorflow or similar)
• Excited to work in a small team and take research ideas into the real world

THE  CHALLENGE

Sticheo is a revolutionary new form of video advertising and with it have come a whole new range of complexities. We need to work with video streams in many different formats, with a broad variety of end users distributed all around the work. In real-time.

ABOUT THE ROLE

As a streaming engineer in this role, you will be responsible for developing features, analyzing performance, and tuning algorithms for streaming media playback. An individual should have development experience at multiple layers of the OS network stack and have experience building network delivery systems for playback of media content. They will have the opportunity to work with the computer vision team to implement bleeding edge research into VOD streams.

RESPONSIBILITIES

• Design & implement an efficient and scalable streaming architecture
• Advocate and guide strategy for design and product direction
• Coordinate closely with the Computer Vision team, and make implementation recommendations if necessary

REQUIREMENTS