Machine Learning Engineer / Data Scientist
Arcadia, an innovative software development company providing services to international clientele, is looking for ML Engineer.
Cutting-edge technologies. Agile development process. The highly professional team provides good opportunities for professional development and career.
We are looking for a Data Scientist with Python knowledge
- Develop and maintain packages that will be used for drug discovery;
- Integrate cutting-edge ML/DL algorithms and approaches;
- Build data pipelines;
- Build APIs for model serving;
- Work as a part of international team of chemists and data scientists to clarify requirements and agree upon important implementation details (in English);
- Python and its data stack (pandas, numpy, etc.);
- Python and its ML stack (PyTorch, scikit-learn, etc.);
- Python and its parallelization stack (multiprocessing, pebble, etc.);
- Unit testing in Python (unittest, pytest);
- Jupyter Notebooks;
- Understanding of neural networks and their graph counterparts, graph embeddings;
- Familiarity with Linux command line;
- Understanding of parallel processing in Python (thread-based, process-based), serialization, memory mapping;
- Understanding of SQL queries, minimal experience with postgres/oracle;
- Experience with task trackers (preferably Jira) and version control tools (preferably git).
Would be nice to have:
- Java and C++ familiarity would be an advantage;
- Experience with AWS is a plus
- Understanding of drug discovery process and how ML is used there would be an advantage;
- Experience with RDKit and chemical data formats (SMILES, SMARTS, SDF, RDF) would be an advantage;
- Experience with Domino Data Lab would be a plus;
- Experience in web technologies also would be a plus;
- Experience in development of simple services with python is a plus (flask, nginx, uwsgi, docker);
Salary and benefits:
- competitive salary (discussable, depending on experience);
- training programs, professional development;
- benefits: voluntary health insurance (incl. dental insurance)‚ corporate events and sports activities;
- flexible schedule;
- comfortable office in the downtown near metro station/ or remote work.