Video capacity needs are exploding worldwide, with no end in sight for years to come. Managing capacity and costs are now becoming a strategic issue for many bandwidth providers, and iSIZE addresses this problem head on, with an innovative, amazingly elegant, platform agnostic solution. The results speak for themselves
Patrick Pichette, Chairman of the board at Twitter and ex- Google CFO
We are looking for an independent, self-driven Deep Learning Engineer to join our iSIZE team and contribute to transforming the world of streaming. Engage with world renown companies and help solve some of the biggest technical challenges behind advanced video systems that companies and environment is facing today. We are proud to be working with household names in the sector to reduce the strain on already-overburdened networks and cut the ballooning costs of the data centre and streaming industries, while improving the quality of end users.
- Develop and improve core deep learning architectures for video preprocessing for a variety of applications, such as live video streaming, Video-on-Demand, cloud gaming etc.
- Research and prototyping of new methods for fast image and video enhancement, particularly related to bandwidth saving and video streaming quality enhancement
- Draft publications and patent submissions in collaboration with other team members
- Participate and assist the team in commercial evaluations with top-tier companies
- MSc. in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
- Strong background in: Python; TensorFlow (preferably v1) or PyTorch; evidenced by the development of advanced applications in image/video processing or computer vision (minimum of 12 months experience)
- Strong analytic background in deep neural networks, evidenced by knowledge of how to formulate and test advanced loss functions in neural network design, and design and test of advanced convolutional, recurrent or other neural network architectures in a task-specific manner
- Experience in training and inference with neural network architectures on CPUs/GPUs in cloud (AWS or GCE) and Tensorflow or PyTorch in VMs or Docker containers
- Experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like h5py or similar
- Publications in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
- Solid experience in image processing theory and methods, evidenced by the development of practical designs in this area
- Knowledge of image and video compression and the use of FFmpeg/libav libraries
Why join iSIZE team
- Be part of an award-winning & rapidly-growing start-up company in deep learning and video streaming technologies
- CDL Oxford AI Cohort graduate and backed by some of the leading tech experts
- Possibilities to interact with top-tier industrial labs who are trialling or using iSIZE technologies worldwide
- Collaborate and learn from professors and senior researchers who are part of the iSIZEteam
- Room to innovate and come up with breakthrough ideas
- Career evolution via publications and patent filings, which are strongly encouraged and are part of the official duties of the post
- Access and support to use state-of-the-art CPU and GPU cloud computing facilities
- Competitive salary and performance bonus
iSIZE specializes in deep learning for video delivery and has developed a deep perceptual ‘precoder’ – a software solution that uses AI-trained to “see with the human eye” in order to optimize visual quality in order to save video bitrate during encoding. Its flagship product, BitSave, available both as a SaaS platform at bitsave.tech and for on-premise use, reduces encoding bitrates by up to 40% without compromising perceptual video quality. The technology is deployed as an add-on feature to conventional video encoding pipelines (AVC, HEVC and AV1), without requiring any changes in the streaming process or the client devices. This results in substantial bandwidth, energy and cost savings for VoD and live streaming services, broadcasters and the end consumers. You can see a presentation about our work in the AOMedia Research Forum here and read one of our first preprints here.
iSIZE is the first company to offer bolt-on and backward-compatible precoding solutions that allows video content to be sent and received at far lower transfer rates without any loss of quality. With video content predicted to make up 80% of the internet by 2022, it has never been more important to reduce the data, financial and energy costs of streaming.
More information is available from www.isize.co
Apply by sending your CV, plus a cover letter, to firstname.lastname@example.org
- iSIZE BitSave for environmentally friendly video streaming July 28, 2021 Posted in: News
- iSIZE joins with BBC R&D and Queen Mary University of London to improve video streaming with new disruptive technology July 20, 2021 Posted in: News
- Sustainability Focus: Consumption Matters July 14, 2021 Posted in: In The Press
- Deep learning for video delivery with iSIZE June 29, 2021 Posted in: In The Press