Machine Learning Engineer

schrodinger Schrodinger

Schrödinger, a leader in the field of computational biochemistry, is seeking a Machine Learning Engineer to find insights in dirty chemical datasets.

The ideal candidate will be a data scientist or developer with some experience in writing software and finding insight into medium sized datasets. This is an excellent opportunity for those looking to transition into full-time professional software development while still leveraging a statistics, math, physics, or chemistry background.

Previous experience in professional software development is not required.

A successful candidate will:

  • Work well in a collaborative environment
  • Run descriptive statistics over sparse and dirty datasets
  • Be able to visualize data in interesting unintuitive ways
  • Rapidly develop prototype code
  • Integrate new/different libraries early and often (e.g. scikit-learn, tensorflow)
  • Work with engineers to maintain successful prototypes

Required qualifications include:

  • Familiarity with data science and machine learning skills and concepts
  • Familiarity with deep learning, neural networks, random forest, support vector machines, and other machine learning techniques
  • Excellent written and verbal communication skills

Desirable qualifications include:

  • Track record rapidly digesting and reproducing academic learning-based research papers
  • Python development experience
  • Self Driven

To apply for this job please visit tinyurl.com.