Position: Machine Learning Engineer (Biotech)
Company: NCube
Experience required: 5y
English level: upper

We are defying conventions and innovating without boundaries. We are disrupting an industry with bold ideas and passionate pursuit of new possibilities. We are searching for original thinkers, creative scientists, and data-devoted gurus for a famous USA-based project.

**Requirements:**
- PhD in Computational Chemistry, Biochemistry, Structural Biology or similar
- At least 2 years of experience in a postdoc or industry position
- At least 1 year of experience with a popular molecular dynamics package (gromacs, LAMMPS, etc.)
- At least 1 year of experience using state of the art modeling and docking software
- Introductory or above knowledge of Python
- Experience developing machine learning models
- Hands-on experience with at least one machine learning framework (Tensorflow, JAX, Pytorch, scikit-learn, etc.)
- Ability to work independently and supervise others
- Upper-Intermediate English and better

**Good to have:**
- Familiarity with end-to-end spectrum of computer aided drug design workflow
- Familiarity with pharmacological and medicinal chemistry concepts
- Experience running molecular simulations in public cloud
- 2 years of experience using Python
- 2 years of experience building machine learning models, in particular neural networks
- Familiarity with C++, CUDA and performance optimization of CUDA kernels
- Publication record in ML for drug discovery

**Responsibilities:**
- Development of novel ML methods in computational chemistry leveraging state of the art research, including for example machine learned force fields and equivariant neural networks
- Development of computational chemistry tools as part of an integrated discovery framework
- Application of ML tools to specific drug discovery tasks, target selection, hit finding, hit to lead and lead optimization
- Contribute to hiring and developing other scientists and engineers

**We offer:**
- Competitive salary with the regular review
- Flexible working schedule, fully remote work opportunities
- Taxes compensations, accountant assistance
- Vacation (up to 20 working days)
- Paid sick leaves (10 working days)
- Medical Insurance (optional)
- Online English courses
- Direct cooperation with the customer
- Teambuildings, corporate parties and company trips abroad
- Great working environment and team spirit