ML Engineer; UAE

Machine Learning Engineer

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 write production-level Python code, run ML experiments, integrate new functionalities, and work with foundation models. The candidate will also provide technical support to the Dev Ops team and perform intra-team MLOps.

Reports to: Team Lead in Cheminformatics

Responsibilities:

• Develop and maintain the internal machine learning pipeline at production level to support drug discovery initiatives.
• Optimize, refactor, and debug existing Python code 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.

Education: Bachelor’s, Master’s, or PhD in a Machine Learning related field.

Experience and Skills:

• Strong background in machine learning with practical application experience.
• 4+ years of experience in Python production-level development.
• Proficiency with coding standards such as PEP8 and Google style guide.
• Experience with No
  
  SQL 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 Num Py, Pandas, PyTorch, and scikit‑learn.
• Solid understanding of object-oriented programming, design patterns, and software architecture best practices.
• Proactive attitude, strong problem‑solving skills, and commitment to continuous learning.

Preferred

Skills:

• Experience with deep learning frameworks and techniques.
• Familiarity with RDKit for cheminformatics and Plotly for data visualization.
• Hands‑on experience with 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

Place of work: TBD

About Role: We are seeking a Senior Machine Learning Scientist with expertise in modern generative modelling and structure‑aware machine learning to develop advanced AI systems for modelling complex three‑dimensional molecular data. The role involves building deep learning approaches that operate on spatial molecular representations, integrating physical and geometric constraints, and supporting computational workflows.

Reports to: Head of AI for Chemistry Solutions

Responsibilities:

Model Research & Development:

• Develop ML models to analyze 3D molecular structures and interactions.
• Design computational workflows to evaluate and prioritize candidate structures based on predicted structural and physicochemical properties.
• Build architectures that integrate multiple predictive tasks across structural modelling and interaction prediction.
• Develop representations and embeddings for complex molecular geometries and spatial relationships.
• Work with large‑scale structural datasets.

Technical Leadership:

• Design scalable pipelines for training models on large structural datasets.
• Define modelling approaches that incorporate spatial context, interaction interfaces, and geometric constraints.
• Collaborate with engineers to ensure efficient training, inference, and integration into internal platforms.

Research & Strategy:

• Stay up to date with advances in protein design, molecular ML, and geometric deep learning.
• Evaluate emerging methods such as all‑atom diffusion models, graph networks, and multimodal foundation models.
• Contribute to internal research directions and experimentation with new modelling paradigms for complex spatial data.

Education: PhD or MS in Machine Learning, Computational Biology, Structural Biology, Computer Science, Biophysics, or related field.

Experience and Skills:

• Strong experience developing ML…