As a Speech Processing Engineer, you are a computer scientist with an analytical mind set, a deep understanding of speech processing and provable hands-on programming experience. You will be part of the Applied A.I. team and you are passionate about machine learning, speech and natural language processing.
You will work on interesting projects for some of the world’s most innovative clients and partners as well as work on Faktion’s proprietary conversational agent platform, called Chatlayer.ai:
- You love working in a high growth company.
- You will build, improve and extend speech models which can include speech-to-text models, text-to-speech models or speech analysis models.
- Your ability to understand and implement state-of-the-art academic research papers will help you to apply novel algorithms to large volumes of real-life data.
- You will work closely on product delivery roadmap, taking it from development to production in collaboration with our engineers, researchers, technical leads and architects.
- You will help the team to improve upon current methods and models. You have a practical mindset and are able to bring these models into a production environment. As such, you have extensive experience with Python, C/C++ or another relevant programming language.
- Your programming experience will allow you to closely collaborate with back-end developers to improve our models and push them through our release process.
- You have a master’s degree or PhD in computer science, mathematics, engineering, computational linguistics, or related field.
- You have provable experience in deep learning, speech processing and NLP (e.g. Kaggle competitions or spare-time projects).
- You have a basic understanding of signal processing with application to speech and audio processing.
- You are experienced with acoustic modeling and language modeling
- You have good knowledge of and experience with Python and/or C/C++.
- You have a strong linguistic background and analytical mindset.
- You have a practical mindset and are willing to get your hands dirty. You understand the difference between fundamental research and data driven development. You consider yourself a healthy mix between a machine learning expert, a software engineer, a researcher, and a hacker.
- You are fluent in English.
- You can work independently and take matters into your own hands.
- The ability to quickly learn new technologies and successfully implement them is essential.
- Experience with any of the following is considered a plus:
- Working knowledge of TensorFlow or Keras.
- Having built or have been working with an automatic speech recognition (ASR) toolkit such as Kaldi or DeepSpeech is considered a strong plus.
- Expertise in some of the following speech tasks: speech-to-text, text-to-speech, emotion recognition, personality recognition or speaker diarization.
- Good understanding or hands on experience of speech preprocessing, noise-robust speech processing normalization techniques, speech related techniques (e.g. HMM, weighted FST, Viterbi,…)
- Fluency in phonetics and making phonetic transcriptions.