Join our fully remote team. Together we work on tough, large scale, machine learning problems.
We build ML products for pharma, biotech, web and automotive companies.
As a developer of our small and tight-knit team you will be responsible for your own project and work on all parts of the solution: From researching and defining what to build, to modeling, integration and scaling your solution on AWS / Google or Azure Cloud.
And don’t worry if you are just getting serious with machine learning, we’ll give you the chance and training to get good at it.
You will like the role if you want to
- Work 100% on machine learning projects, no data warehousing, no distractions.
- Work on hard, interesting and meaningful challenges – like digital drug discovery.
- Work remotely from anywhere in the world.
- Get stuff done and test your ideas – without bureaucracy.
- Go on team adventures (Sailing in the summer and Skiing in the winter).
- Work on large & complicated datasets from companies like Volkswagen, Mercedes and Johnson & Johnson.
Skills you need
- Excellent communication.
- Solid Engineering Background (5+ years development experience).
- Familiar with AWS and / or Google Cloud, Docker and Python.
- Familiar with Machine Learning.
Skills you will learn
- How to build real-world machine learning pipelines.
- How drugs are developed, cars are built, how LCMS machines work, and genomes are sequenced and of course what the data involved looks like. – You will never be bored.
- Work on a freelance / contract basis, but with employee benefits: Long-term contract, 1-3 month cancellation period, paid holiday & sick days, team holidays twice per year.
- Significant company shares – and a share in yearly profits.
- Salary range: 2.500 – 4.500 € / month, depending on experience and location (cost of living).
How to apply
- Simply fill out the Machine Learning Engineer Questionnaire: https://forms.gle/hKcp8QfyfhPtJcNg6
- We review your answers and, if you make it to the next stage, send you a code challenge and invite you for a phone interview with Alan and Markus.