Machine Learning Ops Engineer (MLOps)
Exscientia, Austria
Job Description
Exscientia is an AI-driven pharmatech company committed to discovering, designing and developing the best possible drugs in the fastest and most effective manner. Exscientia developed the first-ever functional precision oncology platform to successfully guide treatment selection and improve patient outcomes in a prospective interventional clinical study, as well as to progress AI-designed small molecules into the clinical setting. Our pipeline demonstrates our ability to rapidly translate scientific concepts into precision-designed therapeutic candidates, with more than 25 projects underway. By designing better drugs, faster, we believe the best ideas of science can rapidly become the best medicines for patients.
Exscientia is seeking an MLOps Engineer to support the ongoing development of our high throughput microscopy analysis software stack.
Exscientia is a company that is committed to getting medicines to patients in the fastest and most effective manner. We do this by applying the latest research in Artificial intelligence (AI), machine learning and modern high-performance computational methods to transform drug design. Exscientia is at the forefront of Artificial Intelligence (AI) driven drug discovery and the only company to have used AI to design drug molecules that are currently in clinical studies.
As MLOps Engineer you will take over the continued development, maintenance, and scaling of Exscientia’s deep learning image analysis pipeline and ensure that data flows are robust, scalable, and reproducible. You will work closely with AI research scientists to bring new methods to production, as well as opportunistically identify areas of improvement to the software stack. Working closely with the global Data and AI Technology departments, you will be responsible for integrating microscopy-based data flows into the larger organization and contributing directly to the AI-driven optimization of drug candidates for cancer treatment.
- Drive the continued development of key software for the analysis of high-throughput microscopy data using state of the art computer vision approaches
- Build infrastructure to ensure the highest standards of data integrity, scalability, and reproducibility - and potentially enable new ways of using our rich datasets
- Enjoy a highly collaborative work culture that values initiative and professional autonomy
Requirements
- A Master’s degree or higher in computer science or adjacent field
- Deep knowledge of Python
- Excellent MLOps knowledge and experience supporting ML pipelines in production, preferably for computer vision applications
- Experience with continuous integration and deployment (CI/CD) tools
- Experience using cloud hosting providers such as GCP, AWS, or Azure
- Excellent communication skills
Ways to stand out
- Experience with software development best practices in a research setting
- Experience or strong interest in working in the life sciences
- Hands-on knowledge of automation data pipelines, scientific workflow systems, and their monitoring
- ML-adjacent skills, e.g. R for data analysis, dashboarding, database systems
Benefits
- Making a positive contribution to patients by revolutionising the pharmaceutical industry through AI-driven discovery
- Kick-start or further grow your career - at Exscientia, you will have the opportunity to acquire valuable skills, work on problems that matter, and learn from world-class technical and scientific leaders
- A highly competitive compensation package in accordance with the Austrian collective bargaining agreement, starting from a minimum salary of 55.000,- gross per year on a full time basis. We will negotiate an attractive package and overpayment based on your background and previous work experience.
- Funding for professional development and conference attendance
- The opportunity to join an inclusive, collaborative and intellectually stimulating culture
- Flexible working and remote working to allow you to manage your own time
- Daily lunch options, regular team events and lots of opportunities for casual networking