⭐️ Machine Learning Engineer (Python)
Data Revenue
The role
Join a team of fully remote machine learning engineers. Together we work on tough, large scale, machine learning problems.
We build end-to-end productions solutions for pharma, biotech, web and automotive companies.
As a developer of our small and tight-knit team you will be responsible for important projects 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, call the shots and without bureaucracy.
- Go on great team trips (Sailing in the summer and Skiing in the winter).
- Work on large & complicated datasets from big companies (Volkswagen, Mercedes, Johnson & Johnson and more).
Skills you need
- Great communications skills.
- Solid Engineering Background (5+ years development experience).
- Familiar with AWS and / or Google Cloud, Docker and Python.
- Ability to travel to clients for 1-2 day workshops.
Skills you will learn
- How to solve real world problems with machine learning.
- How drugs are developed, cars are built, how LCMS machines work, and genomes are sequenced and of course what the data involved looks like.
Compensation
- Working 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 stock options shares, that also include an equal 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 Developer Questionnaire: https://forms.gle/hKcp8QfyfhPtJcNg6
- After the interview questions the next stage is a code challenge and a phone interview with Alan (CTO) and Markus (CEO).
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