We are currently looking for computer scientists or computational linguists as freelancers who could add Norwegian to the languages supported by an NLU system. Candidates should be available for 20-40 hours per week, ideally during European business hours. The job will consist of porting from English or Swedish to Norwegian resources used by our Machine-Learning-based NLU system, which is an AI (Artificial Intelligence) component integrated into products used by millions of people all over the world, and to improve them over time. The work will involve the development of grammars and lexical resources, the correction of annotated data, and other adjustments of the system.
- Creation of resources to be used for Speech Recognition software
- Development of grammars for Natural Language Understanding
- (Re)Training of Machine Learning models for NLU, including evaluation and error analysis
- Text manipulation and data processing
- Localization of data, online surveys, etc. into Norwegian (Bokmål and Nynorsk)
The qualified candidate will be working anywhere from 20 to 40 hours per week.
Start date will be disucussed with qualified candidates.
- Bachelor or Master in Computer Science, Engineering, Statistics, Computational Linguistics, or other relevant technical field
- (Near-)native speakers of Norwegian
- Affinity with statistics and Machine Learning
- Solid Unix skills (bash)
- Sound knowledge of regular expressions and a scripting language such as Python or Perl
- Familiarity with version-control software (git, svn)
- Fluency in English (written and oral)
- Knowledge of Swedish highly desirable
We take pride in our diverse team and our flexible work opportunities, and as a publicly traded company our efforts and earned us the first place ranking in the FlexJobs Top 100 Companies index. Deloitte also recognized Appen with the 2017 Asia Pacific Technology Fast 500 and the Technology Fast 50 Australia awards.
We are an equal opportunity company and value diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.