We firmly believe that innovation is the key to solve today’s biggest challenges, being it climate change, hunger or access to education and clean water. To solve those challenges, we give our customers insights and access to the world’s most recent innovations.
Your Job Mission
As a Machine Learning Engineer (NLP) at INNOSPOT, you are responsible for making our platform more intelligent in order to help our customers to get their job done easier and faster. We could have called it a Data Science position focusing on NLP, but this position is a lot more focused on hands-on engineering outcomes and shipping value to our customers, even if you will incorporate the latest scientific research into your work.
- Become the master of all our (NLP) Machine Learning models. This includes optimizing the performance and accuracy of our existing models, the evaluation and prototyping of new models and the deployment of models into our cloud infrastructure.
- Solve challenges such as building a “Smart Keyword Suggestion” model, extend our Startup Ranking Algorithm or improve our startup Similarity Search by better understanding the products and solutions a startup has to offer.
- Help us deliver value to our users in a speedy and reliable manner by developing new features. Break down your work into small user stories and make your progress visible. You will own features from conception until and after they are in production.
- Get new insights into our startup data and create business value out of it. Don’t overanalyze but rather build rapid prototypes to test your hypothesis, ship a minimum viable product to the customer and accompany the feature to its perfection and final shipment.
- Participate in our bi-weekly development sprints including the usual shebang of user story refinement, planning and reviews and help us improve how we build our products at INNOSPOT by making your voice count in and outside of our retrospectives.
- Collaborate with our product owner, startup scouts and sales people to get a strong understanding of our customer needs and develop solutions in a creative and pro-active way that will deeply impress our customers.
- Keep learning about new technologies and the latest NLP research developments to assess whether and how they can be used at INNOSPOT.
Our Tech Stack
We always try to use the best tools available for the job. Our current tech stack looks like this, but don’t worry, we don’t need you to be familiar with all of these.
- Python for Machine Learning tasks and the ETL Pipeline
- MongoDB for persisting data and ElasticSearch for our Search Engine
- SageMaker, nltk, scikit-learn, pandas and spacy for building and running ML models
- Docker, Bitbucket Pipelines and CloudStack for DevOps
- AWS for cloud computing (API Gateway, EC2, S3, Lambda, SQS, SageMaker)
What we Value
Many of our applicants have stellar track records and our team units the strong passion to become the best. We purposefully did not create a standard list of minimum qualifications, because we care much more about your motivation and your drive towards action than we care about your CV. At INNOSPOT, the team comes first and is more important than the individual, because only as a team we can achieve a hell of a lot more than an individual could achieve on its own. Read more about our four core values in the INNOSPOT Culture Deck
What to expect
- Work with an ambitious team that has a very strong passion for learning and innovation.
- Grow as a person and become the best through #instantfeedback, weekly 1×1, retrospectives and knowledge sharing sessions.
- Get your voice heard and valued. We always expect you to speak up and share your ideas about what we can improve within the company.
- Get a perfect mix between office work and remote work
- There is more than one way to improve our world: We support them all!