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Machine Learning/NLP Engineer
at Wluper

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  • London
  • fulltime
  • ₤50000 - ₤60000 per year
We are looking for a Machine Learning/NLP Engineer to join our team in London.

As a member of the core team you will be responsible for leading the full stack development and implementation efforts. You will be involved from concept, all the way through deployment, working closely with the team and taking part in the complete project life-cycle, where you have significant influence on our overall strategy by helping define system features, drive the system architecture, and spearhead the best practices that enable a quality product.

The role will entail building the complete NLP pipeline system. State-of-the-art Machine Learning algorithms will be at the core (e.g. newest forms of Word embedding’s, LSTMs, etc.) as well as further involvement of exploring and researching new scientific methods. The ideal candidate has a deep understanding of these technologies and enjoys taking charge of the project and seeks the freedom of building a cutting edge system.

We are building an intelligent personal assistant for navigation and transportation and are backed by Jaguar Land Rover's InMotion Ventures. Come join us, together we will work on one of the coolest and most innovative fields of technology in the recent years.

Basic Qualification

* Bachelor’s Degree in Computer Science, Engineering, or related field
* Proficiency in modern programming languages such as C/C++, Java, and Python and open-source technologies (TensorFlow, Apache)
* Strong fundamentals in problem solving, algorithm design and complexity analysis
* Strong personal interest in learning, researching, and creating new technologies
* Strong attention to details, inventive, able to work in a fast-paced environment

Preferred Qualification

* Master’s Degree in Machine Learning, Computer Science, or related field
* Academic and/or industry experience with standard AI and ML techniques, ASR, NLP and scientific thinking
* Knowledge of software engineering practices and best practices for the full software development
* Understanding of design for scalability, performance and reliability
* Ability to produce code that is fault-tolerant, efficient, and maintainable
* Ability to prototype and evaluate applications and interaction methodologies
* Ability and willingness to multi-task and learn new technologies quickly
* Excellence in technical communications with both technical and non-technical peers


Python, Java, TensorFlow, Machine Learning, Natural Language Processing, Computational Linguistics, Neural Networks, Data Mining, Information Retrieval, Web Mining, Web Scraping, Git, Scala, Amazon Web Services, REST APIs, Statistical Natural Language Processing

Equity: 3.0% – 5.0%

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