AI​/ML Engineer

We are on a mission to liberate scientific data. At Data Revival, we bridge the gap between complex chemical knowledge and modern machine learning/AI. By building advanced AI tools, we turn static, vast chemical knowledge bases into accessible, searchable, and actionable insights for researchers pushing the boundaries of science.

We are looking for an AI/ML Engineer who is ready to tackle one of the hardest problems in science: teaching machines to understand chemistry. In this role, you won’t just be tuning hyperparameters; you will own the architecture that extracts structure from chaos. You will work right at the core of our R&D team, taking novel models from a whiteboard concept to a production‑ready tool that empowers scientists to discover new drugs and engineer next‑generation materials.

If you crave ownership and want to build technology that actually accelerates scientific discovery, this is your home.

• Research, design, and implement novel machine learning architectures tailored for chemical and molecular data.
• Develop and maintain robust data pipelines for processing, augmenting, and featurising large scale chemical datasets.
• Train, validate, and benchmark models to ensure they meet performance and accuracy requirements.
• Stay current with state‑of‑the‑art research in machine learning, computational chemistry, and bioinformatics.

• Proficiency in Python and the core data science ecosystem (e.g., Pandas, Num Py, Scikit‑learn).
• Hands‑on experience with a modern deep learning framework, preferably PyTorch.
• Strong theoretical understanding of machine learning principles, including deep learning and classical statistical models.
• Knowledge of the inner workings of LLMs and VLMs, the ability to gut them and work with them past just surface‑level functionality.
• Experience with the full model development lifecycle, from data preprocessing and feature engineering to model validation.
• Degree in Computer Science, Machine Learning, Computational Chemistry, or equivalent industry experience.

• Prior experience in computational chemistry, bioinformatics, or cheminformatics.
• Experience with MLOps tools and practices for model serving and monitoring.
• Knowledge of tools like RDKit or other chemistry‑specific data toolkits.
• Familiarity with containerisation of services (Docker/Kubernetes).
• Publications in relevant ML or scientific journals.

• Competitive salary and a comprehensive benefits package.
• The opportunity to work on cutting‑edge research problems at the intersection of AI and chemistry.
• A key role in a small, collaborative team with direct impact on clients and product direction.
• Support for professional growth and continuous learning.

• Entry level

• Full‑time

• Engineering and Information Technology

• Technology, Information and Internet

Referrals increase your chances of interviewing at Data Revival by 2x.