We are looking for a highly motivated Machine Learning Intern now on a continuous basis. You’ll contribute to the development of our ML pipeline and work closely with our ML Engineering and Research colleagues. You will have the opportunity to drive your own projects while learning from our experienced team members.

Who we are:

At molab.ai, we accelerate the drug and compound discovery process for patients, people, and the planet by fusing cutting-edge AI technologies with latest insights from the natural science frontier. To this end, our team of excelling scientists has been developing data science models to predict molecular properties with market-outperforming accuracy. We have secured the funds to expand our team and elevate digital drug discovery to an entirely new level. If you are looking for a purpose-driven AI company that combines scientific excellence, impact and entrepreneurial drive, let’s create better molecules, faster, together!

Role description:

  • You will work on extending and improving our end-to-end ML pipeline using software engineering best practices
  • You will work closely with our ML Engineering and Research colleagues and support the implementation, training and deployment of state-of-the-art models
  • You will work on testing and evaluating ML models

What you need to succeed

  • You are approaching the final steps of your master’s degree or are currently pursuing a PhD with excellent results
  • The background of your studies is within natural science, preferably Computer Science, Engineering, Data Science etc.
  • Practical experience with deep learning is a strong plus
  • You have experience with Python, PyTorch, Scikit-Learn, Pandas/numpy
  • Ability to think critically and perform unbiased analysis
  • Cross functional collaboration experience
  • Very good written and spoken English

What we offer:

  • Dedicated onboarding and mentoring
  • Steep learning curve in a VC-backed, early-stage startup
  • Flexible working models - including a great office in Munich and flexibility when it comes to working from home
  • Driving impact for patients and our planet from day one
  • Competitive salary

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