ML Engineer (UAE)

Place of work Abu Dhabi, United Arab Emirates About Role Insilico Medicine is seeking a Machine Learning Engineer to develop, support and improve predictive models and retrosynthesis in Chemistry & Biology. The candidate will be writing production-level Python code, run ML-related experiments, integrate new functionalities, work with foundation models. The candidate will also provide technical support to the DevOps team in running the ML infrastructure and perform intrateam MLOps. Reports to Team Lead in

Cheminformatics Responsibilities:

Develop and maintain the internal machine learning (ML) pipeline at the production level to support cutting-edge drug discovery initiatives. Optimize, refactor, and debug existing code in Python to enhance performance, scalability, and efficiency. Deploy ML models into the platform for real-world applications in chemistry and biology. Implement and fine-tune ML-dedicated algorithms in Python, ensuring high accuracy and robustness. Collaborate on MLOps practices to ensure seamless model integration, deployment, and continuous improvement.

General Requirements:

I. Education Bachelor's degree/Master's degree/PhD degree in a Machine Learning related field. II. Experience and Skills Strong background in machine learning (ML) with practical application experience. 4+ years of experience in Python production-level development. Proficiency with coding standards such as PEP8, Google style guide , or similar best practices. Experience with NoSQL databases , such as MongoDB . Experience working with Linux or other Unix-based operating systems. Proficiency in version control systems like Git . Hands-on experience with Python numerical and machine learning libraries such as Numpy, Pandas, PyTorch, and Scikit-learn . Solid understanding of object-oriented programming (OOP), design patterns, and software architecture best practices. A proactive attitude, strong problem-solving skills, and a commitment to continuous learning. III. Preferred Skills Experience with deep learning (DL) frameworks and techniques. Familiarity with RDKit for cheminformatics and Plotly for data visualization. Hands-on experience with a range of ML/DL methods such as Transformers , RNNs , CNNs , GNNs , and Gradient Boosting . Expertise in feature engineering and optimization techniques. Knowledge of cheminformatics and the drug discovery process. Ability to quickly learn and adapt to new libraries, tools, and emerging ML technologies. Experience in programming with C++ is an advantage Please send your CV to