Are you passionate about revolutionizing drug discovery and development? Do you have a strong background in machine learning and a desire to lead cutting-edge projects? Join a rapidly expanding company, and be part of our interdisciplinary team working at the forefront of chemistry, robotics, and software engineering.
Role Overview:
As a Machine Learning Scientist, you will play a pivotal role in building and improving computational tools to complement their integrated platform. You will use the platform to design, test, and implement algorithms to extract information from literature procedures. Then also build algorithms to convert the extracted data to standard processes.
Responsibilities:
Prepare, process, clean, and annotate datasets for machine learning development; curate datasets for company-wide use.
Influence data ingestion engines to ensure pristine and well annotated data for short- and long-term applications are systematically acquired from the laboratory or third-party sources.
Develop, benchmark, and rapidly iterate on deterministic and AI/Deep Learning methods for extracting reagents, substrates, products, and conditions from literature reaction procedures.
Develop, benchmark, and rapidly iterate on deterministic and AI/Deep Learning methods for automatically convert reaction procedures into a standardised format ready for our automated laboratory.
Development and implementation of R&D algorithms into software products
Presentation of data and recommendations to the executive team and customers, internal and external.
Requirements:
PhD degree in Data science/AI, Computer Science, Cheminformatics, Bioinformatic or equivalent professional experience.
Minimum 5+ years of experience using major deep learning framework.
Successful development and deployment of AI/ML/DL based tools in high-value applications.
Deep domain expertise in applied mathematics and primitives used in AI/ML/DL.
Cross-functional inclination to partner with strong software engineers.
Strong proficiency with ML toolkits (Pytorch, Tensorflow, Scikit-Learn, etc) and deployment of software on high-performance compute clusters.
Solid knowledge of NLP and LLM models.
Understanding of the latest AI research and ability to efficiently implement these systems.
Strong analytical thinking skills and the capacity to approach challenges methodically.
Proficiency with cloud platforms like AWS for ML applications.
Enthusiasm to learn new approaches and concepts and to work with an experimental automation platform.
Keen interest in chemistry and willingness to learn chemical concepts fast.
Proficiency in contemporary software engineering approaches, including CI/CD, version control, and unit testing.
Desired Skills & Attributes:
Understanding of chemistry and organic reactions procedures.
Experience in the development & deployment of large-scale ML algorithms.
Experience leading interdisciplinary teams to deliver results under tight deadlines, preferably using Agile/Scrum-based project management.
Experience analysing large structured and unstructured datasets.
Familiarity with database tools such as RDBMS (e.g. MySQL) or NO-SQL (e.g. MongoDB).