As a NLP and NLU Researcher of the awarded and fast growing Austrian startup ONDEWO your primary focus will be the development of cutting edge machine learning and deep learning algorithms for our highly scalable and performant Natural Language Understanding (NLU) Platform.
Our mission is to enable machines to engage with humans in natural conversations (e.g. robots, voice assistants, chatbots, cars and IOT devices). You will do applied research and develop new ways for improving text classification. Are you ready to shape the future of machine-human communication and interaction? Then you are the right person for our team!
- Work on machine learning and data science projects on the cutting-edge of technology
- Analyze large behavioral user data sets from our international clients, come up with new data models and implement concepts and algorithms in Python and TensorFlow
- Build, train, evaluate, benchmark and tune machine learning and deep learning models
- Be part of a cross functional team to work on continuous improvement of our systems with innovative technologies and research techniques
- Keep up to date with the latest technologies, evaluate new tools and learn new techniques
- Write reusable, testable, and efficient code – we love to “type” everything, hence “typings”
- Participate in design, code and architecture reviews and coach other team members
- University degree (MS/PHD) in computer science, physics, mathematics, electrical engineering, data science or equivalent industry experience
- Minimum of 3 years experience in Python natural language processing and Text Classification with a data science technology stack (e.g. TensorFlow, Keras, scikit-learn, NLTK, Spacy, Pandas, numpy, Jupyter, Pandas, XGBoost, TextBlob)
- Proven proficiency in NLP, NLU and Text Classification techniques and algorithms such as,
1. Feature engineering (e.g. TF-IDF, NLP-based features, word embeddings, topic models, and word, n-gram, and character level features)
2. Algorithms and models from classical machine learning (e.g. Support Vector Machine, Bagging Models, Boosting Models) and deep learning (e.g. CNN, LSTM, GRU, Bidirectional RNN)
3. Techniques for tuning models (e.g. text cleaning, hyperparameter search, ensemble methods such as bagging, stacking and boosting, hierarchical classification)
- Passion for natural language processing (NLP) and understanding (NLU) related machine learning models and techniques
- Loves working with cutting-edge technologies, research techniques and algorithms
- Passion and interest to learn and apply reinforcement learning
- Strong team player, eager to learn and get things done mindset, and great to work with
- English fluency, both written and verbally (fluency in German or another language is a plus)
According to “Kollektivvertrag” the yearly salary is 47.488 EUR (14x monthly salary 3.392 EUR). However we pay much more and offer employee stock options dependent on the qualification, education and experience. Salary increases fast when showing exceptional performance.