gweek is solving real world problems. At least 40% of the world is terrified of speaking in public, yet we all have to present at some stage in our careers. For many of us, it’s our differentiator: get noticed or never get noticed. The world is also moving on from the assumed authority of oratory, eloquence and canned speech making. Authenticity, and coming across as genuine self, is the ‘new black.’ This makes gweek a very special entity. When you add up our ability to track and quantify effective communication and teach how to improve; we present high barriers to entry. We’re at the cutting edge of our emerging industry, people analytics.
The most sophisticated companies in the world already look to gweek to empower their people. We are also growing fast at secondary schools, enabling students with the most essential career skills of all. gweek will also help the next generation choose its leaders. See https://gweekspeech.com for how we are setting a beyond bias global standard in human communication.
Machine learning is core to our capabilities. We offer our ML team unique, complex and fascinating problems, which are highly rewarding to resolve. Besides, you’ll be helping humans communicate and understand one another better.
- Evaluation and implementation of signal processing, machine learning and statistical modeling algorithms as applied to speech analysis and natural language processing
- Evaluation, testing and integration of Automatic Speech Recognition Systems
- Research and apply appropriate frameworks in the areas of speech analytics, statistical NLP, deep neural networks and general machine learning
- Data acquisition
- Development and deployment of speech analytics products
- Academic background in NLP techniques
- Understanding and application of Speech Recognition Engine technologies and algorithms
- Experience working with speech recognition toolkits such as DynaSpeak, Attila, HTK, Kaldi and OpenFst or other equivalents
- Strong software development experience in Python, R, Java, integration with C/C++ toolkits
- Machine learning and statistical data analysis experience as applied to speech processing
- Backend development experience, development of data processing and analysis pipelines, develop REST APIs
- Linux/Unix, Scripting, DevOps tools, Cloud infrastructure such as AWS, Azur, Softlayer
- Experience with prosodic analysis very useful
- Excellent analytical and problem-solving skills
- Strong desire to do research and learn
- Self-starter and self-driven
- Team player
Please contact CEO James Bryce or CTO David Lazar at info@gweekspeech.com for more details and to sign our non-disclosure agreement ahead of any discussion.
Thank you for your interest. You would be joining a highly motivated and committed team solving some of the world’s most fundamental, enduring problems.