You'll be working within the Data Science team which is responsible for inventing new solutions, large-scale data analysis and high-throughput data processing pipelines.
As a machine learning engineer, you will start with some small concrete projects and grow towards building more complex systems.
These may include machine learning model development, deployment & optimization and the design and improvement of our internal frameworks and tools.
During your first weeks on-the-job you'll be introduced to our internal service-based architecture, data ecosystem, datasets and git workflows.
The team will help you with your first commits, SSH-config, questions, refactoring, model design, training and evaluation.
After this period, you'll get your own project(s) to work on within the team together with a teammate.
You will focus on creating value from the large amounts of unstructured written information stored in electronic healthcare records, while keeping a close eye on protecting the privacy of its owners.
You can think of developing classification, recommender and information retrieval systems or working on supporting tools such as entity recognition and linking, and deidentification.
We're an experienced team of about six people with a varied background ranging from computational chemistry, physics, artificial intelligence, computer science to applied mathematics.
We work within a much larger software development group within Nedap Healthcare. It is easy to get things done, because we're in full control of the whole stack and products that we create.
Additionally, given that Nedap Healthcare is a big player in the Dutch healthcare market, there are terabytes of data we can leverage to improve care.
We like to discuss recent papers and publications, do hackathons on entirely new subjects and chat about life, the universe and everything.
The team mainly works from our great, green office in Groenlo, but it is also possible to work from home. Especially in the early stages you are expected to frequently be present in Groenlo in order to find your way in the team, data and the products, with sufficient help on-site.
In addition, it is quite pleasant to be together as a team and enjoy lunch together.
Obviously, we offer excellent primary and secondary conditions. You are responsible for your own working hours and holidays.
Nobody keeps track, as we rely on your own accountability. Moreover, we offer you the means to fulfil your own responsibilities.
We also have a good financial arrangement. Nedap does not only offer you a salary and holiday allowance, but also an annual bonus, dividends, and the option of shares.
Moreover, we have a very interesting pension arrangement. But most of all, we invest in your development! Nedap takes your development very seriously.
We offer an extensive introduction programme and a personal development journey, and we will gladly look at your potential with you.
Required experience and skills
We are looking for a candidate with a background in Computer Science / AI or other computational field. We consider it a big plus if you compiled your own Linux-kernel at some point, trained a neural network to monitor your pet’s food intake or scraped a few websites to build your own predictive model.
Additionally, we're looking for a candidate that has a critical mindset, can be pragmatic when required and one that is slightly annoyed when a bookcase isn't ordered properly.
You’ll work on the cutting edge translating recent advances, sometimes in collaboration with a university, to create models & products that make a difference.
You are experienced with developing and evaluating natural language processing technology such as classification systems or search systems.
We consider it a big plus if you are hands on in deploying these systems as well and have experience as a software engineer.
To get a more concrete impression of our technology stack here are some keywords (we don't expect you to know everything) : python, keras, flair, elasticsearch, scikit learn, pytorch, mlflow, ansible, connexion, jupyter lab, pandas, airflow, spacy, parquet.