AI Research Engineer

Purpose:

The AI Research Engineer role bridges chemical research & process innovation with AI-driven digital automation. This position focuses on applying advanced AI techniques to accelerate chemical research & experiments, optimize processes, and enable predictive insights. The role involves designing and validating AI models & digital solutions that integrate with laboratory workflows, experimental data, and automation systems to enhance R&D efficiency and innovation.

Responsibilities:

• AI-Driven Experimentation: Develop and apply machine learning and deep learning models to predict chemical reactions, optimize formulations, and accelerate drug discovery or material development.
• Data Integration: Collect, clean, and structure experimental data from laboratory systems (e.g., LIMS, ELN, spectroscopy, chromatography) and integrate with plant-level data sources (e.g., PIMS, MES).
• Digital Automation: Collaborate with R&D teams to embed AI into robotic workflows, automated synthesis, and high-throughput screening platforms.
• Simulation & Modeling: Use AI to enhance computational chemistry models, molecular simulations, and predictive toxicology.
• Cross-Functional Collaboration: Work closely with research scientist, chemists, process engineers, and digitalization teams to translate scientific hypotheses into AI-enabled solutions.
• Compliance & Safety: Ensure adherence to HSE, GxP, and data governance standards; implement responsible AI practices for transparency and reproducibility.
• Knowledge Sharing: Document methodologies, publish internal reports, and contribute to reusable AI libraries for chemical and pharmaceutical applications.

Requirements:

• Bachelor’s or Master’s in Computer Science, Data Science, Chemical Engineering, or related field.
• 5+ years of experience in applied AI/ML engineering, preferably in chemical or pharmaceutical R&D environments.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch); familiarity with cheminformatics tools (RDKit) is a plus.
• Experience with data integration from lab systems (LIMS, ELN) and process platforms (PIMS, MES).
• Strong problem-solving skills and ability to work collaboratively with scientific teams.
• Knowledge of digital automation concepts and laboratory workflows is desirable.

Working Conditions:

Primarily office/lab-based with occasional site visits; Work with sensitive confidential data under strict governance; collaborate across time zones and engage in pilot testing within live operational contexts following HSE & IP protection protocols.

EcoCeres is committed to a diverse and inclusive workplace. EcoCeres is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.