Klaus 😻

Klaus is an AI-powered platform for improving customer service.

We’re at the forefront of the growing customer experience market. In 2018, Klaus was founded in response to a pain point our Co-Founders (Martin Kõiva and Kair Käsper) experienced firsthand while working together at a leading CRM startup, Pipedrive.

Our quickly expanding, international team has embraced the remote-first mindset from day one. Having just raised our Series A (12M Euros), we are looking to expand our Machine Learning team in the office in Tallinn, Estonia or remotely from anywhere between UTC-1 and UTC+4.

Our Stack 📚

• Python
• Pandas, TensorFlow, PyTorch, LabelStudio
• NLP: sPacy, hugging face, BERT, fastText
• Google Cloud Platform, Data Studio
• PostgreSQL, Google Cloud Spanner, BigQuery

What to expect? 🧐

• High level of independence, trust, and research freedom
• Excellent data engineering infrastructure - research close to production and data availability
• We work with more than a hundred languages with many customers officially offering support in 10+ languages
• Priority, product-oriented research is to develop methods for automatically evaluating quality in support interactions, i.e
  • Intent detection
  • Text classification
  • Extraction of entities, etc
• Developing solutions for preprocessing of structured & unstructured data and partnering with ML engineers to employ them in data pipelines
• Support from ML engineers in getting research models you create running in production
• Working closely with product teams and communicating your research

Okay! But what are the expectations? 😎

• At least 3-5 years of experience as a Data Scientist in the NLP domain
• Advanced degree in Computational Linguistics, Language Technology or similar - PhD is a huge plus
• Data/text mining, statistical data analysis, experimental design, and hypothesis validation
• Creativity and curiosity to find problems that can be solved with applied science
• Apply scientific methods for solving complex problems in innovative ways that take into account the ROI of the effort
• Identify valuable data sources/shelf models and participate in developing data collection and preparation processes
• Proven track record of getting models to production
• Strong understanding of SQL and database technologies
• Comfortable working independently, in English, and in a remote setting
• Bonus: experience working with large language models, ASR and dealing with transcribed text

Still doubting? Here are a few more reasons why to join! 🎉

• Work in an exciting, rapidly-growing startup environment
• Remote-first culture – work from anywhere with colleagues from 13 different countries
• Base pay + meaningful stock option package
• Supported learning and development
• Mental health support
• Home office setup reimbursement
• Lots of cat gifs and the best colleagues