Emotech is currently raising the state-of-the-art in multiple areas of audio-visual processing. Our projects include topics from a complete AI Speech Technologies portfolio (VAD, Language Recognition, Speaker Recognition, TTS, etc), multilingual automatic speech recognition using hybrid and end-to-end (E2E) architectures to Digital Humans with realistic facial expressions using Computer Vision and latest GAN approaches. We are looking for passionate Applied Research Scientists who are driven by recent research developments and can turn state-of-the-art research work into solutions used by customers worldwide.
As an Applied Research Scientist, you will be working with the full R&D pipeline. You will be delivering a complete research plan, starting with essential literature review, creating proof of concepts using the latest Machine Learning algorithms, collaborating with other scientists to research and test your ideas, and helping software engineers deliver your solutions to customers worldwide. The role is not limited to a specific research field and you will have the opportunity to work in different research fields over time. You will also be encouraged to publish your work at relevant conferences.
- Conduct applied research in some of the most challenging ML problems both individually and as a team
- Collaborate closely with the research team to turn research into working solutions
- Develop and run experiments to identify the most effective solutions
- Deliver robust Machine Learning solutions in a timely manner, responding to Emotech’s business needs
- Optimise your code to fit different requirements (Multi-core, Multi-thread, Parallel execution, GPU)
- Minimum of 1 year of research & development experience in industry
- Proficient knowledge of Tensorflow, PyTorch or similar Deep Learning frameworks
- Deep knowledge of a programming language (e.g. Python, Rust, C++11) in Linux environment; working knowledge of multiple languages
- Ability to write high quality code
- Experience in relevant fields, such as Computer Vision, Speech Processing, Machine Learning and Deep learning
- Good Data Management skills to handle large amounts of training/validation data
- Masters Degree or higher in Computer Science or other relevant area
- Strong grasp of data structures and algorithms
- Extensive experience with state of the art Deep Learning architectures, like ResNets, GANs or transformers.
- Experience with Speech Recognition either using Kaldi toolkit or wav2vec models.
- Commercial experience with serving out DL models using Tensorflow or PyTorch etc.
- Publications in top-tier conferences (CVPR, ICCV, NeurlPS, ICASSP, InterSpeech etc) or journals.