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, 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 develop the ML pipeline for the chemical space using molecular dynamics and virtual screening. As well as contributing to protein-protein interaction inhibitors. 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/ML methods for template-based and template-free cheminformatics towards continuously improving performance. Develop, benchmark, and rapidly iterate on AI methods for reaction likelihood estimation. Design, test and implement algorithms for chemical space exploration. Development and implementation of R&D algorithms into software products. Requirements: PhD degree in Data science/AI, Computer Science, Cheminformatics, Bioinformatic, or equivalent professional experience. Minimum 5+ years of experience using major ML/AI frameworks. 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 Knowledge of cheminformatics. Strong proficiency with ML toolkits (Pytorch, Tensorflow, Scikit-Learn, etc) and deployment of software on high-performance compute clusters. Understanding of the latest AI research and ability to efficiently implement these systems. Strong analytical thinking skills and the capacity to approach challenges methodically. 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: Experience with QSAP/QSPR modelling, ADMET property prediction. Experience with RDkit toolkit and reaction SMARTS syntax. 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).