Senior AI Engineer (Ref: 198313)

Senior AI Engineer - Applied AI, Machine Learning & Chemistry

Location: United States / remote

Industry: Chemical Manufacturing / Industrial AI

Employment: contract

Level: Senior

No Agency support or sponsorships available

About the Opportunity

We are seeking a Senior AI Engineer to help develop and deploy advanced AI and machine learning solutions within a global chemical manufacturing and industrial technology environment.

This is a highly specialised opportunity combining AI engineering, applied machine learning, chemistry, and experimental design .

You will work directly with chemists, chemical engineers, and data engineering teams to develop intelligent systems that automate scientific workflows, analyse experimental results, and optimise complex chemical processes.

The ideal candidate is not simply an AI engineer who can build LLM applications. We need someone who understands the underlying science, can challenge the quality of experimental data, and can translate complex chemical problems into practical, data-driven solutions.

Key Responsibilities:

AI Engineering & Intelligent Automation

• Design, build, and deploy agentic AI workflows to automate scientific research, data analysis, and repetitive processes currently performed by chemists.
• Develop AI agents capable of supporting multi-step scientific workflows, integrating enterprise data, and assisting with technical decision-making.
• Build scalable AI applications using LLMs, agentic frameworks, and enterprise cloud infrastructure.
• Work with data engineers to integrate structured experimental data into AI/ML applications.
• Develop specialised machine learning algorithms tailored to individual chemistry and industrial process challenges.

Chemistry, Experimental Design & Scientific Collaboration

• Work directly with chemists and chemical engineers to understand research objectives, chemical processes, and experimental requirements.
• Apply Design of Experiments (DoE) methodologies to identify relationships between chemical variables, optimise experiments, and improve scientific outcomes.
• Evaluate proposed experiments and determine whether existing datasets can support the intended analysis or predictions.
• Assess the scientific validity of datasets by identifying anomalies, incorrect measurements, and chemically implausible values.
• Demonstrate sufficient chemistry knowledge to discuss concepts such as pH, ions, surfactants, ligands, chemical reactions, and concentration with technical stakeholders.
• Translate experimental results into predictive models that recommend adjustments to chemical formulations and operating conditions.

Machine Learning & Process Optimisation

• Build predictive models using experimental and industrial process data to identify optimal chemical formulations and operating parameters.
• Apply regression, optimisation, statistical modelling, and time-series techniques to complex scientific datasets.
• Develop iterative modelling workflows in which predictions inform laboratory experiments and new experimental results are used to refine the models.
• Support chemical process optimisation projects, including mineral flotation, chemical recovery, and impurity reduction.
• Evaluate model performance, data quality, and experimental assumptions to ensure recommendations are scientifically credible.
• Balance competing process objectives, such as maximising recovery while minimising impurities.

Required Experience

• Strong professional experience in AI engineering, machine learning, or applied data science , including the development and deployment of production-grade solutions.
• Hands-on experience developing agentic AI systems, intelligent automation, and LLM-based workflows .
• A solid foundation in traditional machine learning, statistical modelling, predictive analytics, and optimisation.
• Experience with Design of Experiments (DoE) , experimental datasets, or scientific modelling.
• Working knowledge of chemistry or chemical engineering , gained through education, industry experience, or close collaboration with scientific teams.
• The ability to communicate confidently with chemists, understand scientific terminology, and critically evaluate chemical data.
• Strong programming skills in Python and SQL .
• Experience designing and validating ML models, including appropriate training, validation, and testing methodologies.
• The ability to independently assess complex technical problems, challenge assumptions, and propose practical solutions.
• Experience collaborating with scientists, engineers, and technical stakeholders.

Technical Environment

• AI & LLMs: Claude, LLM applications, AI agents, and agentic workflow orchestration.
• Machine Learning: Predictive modelling, regression, optimisation, statistical learning, and time-series analysis.
• Programming: Python and SQL.
• Data Platforms: Snowflake and Databricks.
• Cloud: Microsoft Azure, with potential future multi-cloud integration.
• Scientific Methods: Design of Experiments, experimental data analysis, process optimisation, and model validation.

Experience with equivalent AI models, frameworks, and cloud platforms is also welcome.

Chemistry Background

A PhD or extensive academic research background in chemistry is not essential .

Candidates may come from AI/ML engineering backgrounds with a degree, minor, or relevant coursework in Chemistry, Chemical Engineering, or a related scientific discipline.

Alternatively, candidates who have worked extensively with chemists or chemical engineers in chemical manufacturing, industrial R&D, or scientific AI environments will be considered.

The key requirement is the ability to understand chemistry at a level sufficient to collaborate with subject-matter experts, recognise scientifically invalid data, and apply AI/ML appropriately to chemical problems .

What Makes This Role Different?

This is not a conventional GenAI or software engineering position.

You will work at the intersection of scientific discovery, industrial chemistry, and artificial intelligence , building systems that directly influence how chemical experiments are designed, evaluated, and optimised.

You will have the opportunity to take ownership of complex technical challenges, work closely with experienced scientists, and help establish AI capabilities across multiple industrial research and process optimisation initiatives.

contact: [email protected]