We are looking for a talented, experienced problem solver to be part of our dynamic, Edinburgh based team responsible for applying Cirrus Logic’s machine learning experience to speech recognition, speaker identification, spoof detection and audio related problems. You will play a lead role in expanding and applying Cirrus’s innovative machine learning techniques into other areas of audio processing.
- Play a lead role in expanding and applying Cirrus’s innovative machine learning techniques into other areas of audio processing.
- Collaborate with other groups as they improve existing products and create new offerings by integrating machine learning and deep learning methods into their solutions.
- Work with other machine learning team members in designing and testing new speech enhancement, signal processing and audio improvement algorithms.
Required Skills and Qualifications
- PhD (or equivalent) in Electrical Engineering, Computer Science, Physics or Mathematics with specialisation in machine learning or closely related field, especially with application to speech processing/signal processing
- Strong technical credentials, with a solid and demonstrable background in using deep learning techniques (including convolutional and recurrent networks) on audio processing tasks (e.g., speech recognition, speaker identification, noise reduction, audio classification).
- Experience applying theoretical models in an applied environment, solid fundamentals in problem solving, algorithm design and complexity analysis.
- Experience working with major deep learning frameworks and backends (e.g. TensorFlow, Theano, Keras, Blocks, Caffe) including implementing custom layers
- Expert in one or more major programming languages (C/C++, Java, or similar), Python and Matlab.
Preferred Skills and Qualifications
- Post doctorate or industry experience
- Proficient with mathematical programming libraries
- Experience in one or more of the following: wavelet analysis, stochastic optimization, Bayesian statistics, nonlinear manifold learning
- Track record of communicating well with software engineers, commercial customers and non-technical leaders
- Excellent verbal/written communication skills, including an ability to effectively collaborate with research and technical teams, and earn the trust of senior partners.
- Experience conducting scientific analyses, and developing different types of supervised and unsupervised models for complex projects
- Experience with defining organizational research and development practices in an industry setting