Position: Data Science Specialist (with RASA experience)
Company: Axon
Experience required: 3y
English level: intermediate

About the project

Our Client wants your smart devices to get smarter. Today’s voice assistants are great, but they are being asked to do things they were not originally created to do. Go ahead, wake up one assistant to ask another to get you a car, a coffee, or play your favourite playlist.

It`s a leading US company that collaborates with headphone manufacturers and creates SDKs for wireless headphones. We believe through deep learning in data science and machine learning will get us to the next level of voice models.

We have signed some of the world's biggest brands and are creating voice assistants to integrate not only into the Client's platform but also their core consumer facing apps. We have built out voice assistants for NPR and Spotify and have rapidly discovered the limitations of tools like Amazon Lex and Dialog Flow. 

The team includes: 7 Mobile Engineers, 2 QA Engineers, 2 Front-End Engineers, 2 Back-End Engineers, 4 Machine Learning Engineers.  

What you need for this position
- Proven experience as an NLP Engineer or similar role (2-5 years);
- Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling;
- Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis etc), statistics and classification algorithms;
- Knowledge of Python and R;
- Experience with Rasa framework;
- Experience generating data using data generation tools;
- Experience with such tools as Amazon Lex, Google Dialogflow, floatbot.ai, IBM Watson, OneReach.ai, Microsoft LUIS;
- Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn);
- Hands-on experience in using the version control system Git;
- Good understanding of Agile concepts;
- At least Intermediate level of English for communication with the international team.

What you will be doing
- Study and transform data science prototypes;
- Design NLP applications;
- Select appropriate annotated datasets for Supervised Learning methods;
- Use effective text representations to transform natural language into useful features;
- Find and implement the right algorithms and tools for NLP tasks;
- Develop NLP systems according to requirements;
- Train the developed model and run evaluation experiments;
- Perform statistical analysis of results and refine models;
- Extend ML libraries and frameworks to apply in NLP tasks;
- Remain updated in the rapidly changing field of machine learning;
- Advise the team on direction and technologies;
- Dedicated to delivery;
- Work in the Rasa framework and Google Cloud Platform.

What we can offer you
- Competitive salary; 
- Exciting projects involving the newest technologies; 
- Challenging work in an international professional environment; 
- Opportunities for professional growth (including free external and internal professional training courses and certifications);
- Foreign languages learning in the company office; 
- Corporate/team/special events; 
- Medical insurance or gym; 
- Other Perks.