Chemist - AI and Process Intelligence in Cheshire, Warrington

Atomik AM is an advanced manufacturing start-up at the frontier of binder jetting additive manufacturing, building the world’s most advanced binder chemistry systems and the data infrastructure that makes them work at scale. We are at an inflection point: our binder systems are proven, our process platform is maturing, and we are now embedding AI across the full development and characterisation pipeline.

We are looking for a Chemist with genuine AI capability to join us as a member of the chemistry team and to grow, over time, into the AI lead for the chemistry division. This is not a data science role with a chemistry overlay, nor a chemistry role with a passing interest in machine learning. We are looking for someone who holds both with equal seriousness: technically grounded in chemistry, and fluent enough in AI tools and methods to begin transforming how we develop and characterise binders.

You will work alongside our chemistry and engineering team, contributing to formulation development and experimental programmes while building and embedding AI-enabled workflows from experimental design and data capture through to predictive modelling and characterisation analysis. This is a role for someone who wants to build something lasting and is ready to grow with it.

• Support formulation development and optimisation of binder systems, including material selection and process parameter optimisation.
• Design and execute experiments to evaluate new formulations and identify improvements, working closely with the chemistry and engineering teams.
• Develop and implement testing and characterisation protocols to ensure product performance and quality meet customer requirements.
• Ensure all work complies with relevant safety and environmental regulations.
• Collaborate across chemistry, engineering and commercial functions to support scale-up and translation of laboratory development into real-world applications.

• Identify and implement AI-enabled tools and workflows across binder development and characterisation, including experimental design (DoE), data capture, automated analysis, and predictive modelling.
• Work with the team to digitise and structure experimental data to support machine learning and pattern recognition across formulation datasets.
• Develop and maintain AI-assisted protocols for routine characterisation tasks, freeing chemistry resource for higher-value experimental work.
• Stay current with emerging AI tools relevant to materials chemistry and propose practical applications within Atomik’s workflow.
• Over time, take ownership of the AI strategy for the chemistry division, becoming the internal lead and point of expertise.

• BSc in Chemistry or a closely related discipline.
• Demonstrable working knowledge of AI tools, including but not limited to LLMs, machine learning frameworks, and AI-assisted data analysis and the ability to apply them in a technical R&D context.
• Strong foundation in inorganic or organic chemistry.
• Ability to design, execute, and interpret experiments with appropriate rigour.
• Clear and professional communication, both internally with team colleagues and externally with suppliers and clients.
• Solutions-focused mindset: we are a small team in a fast-moving environment and expect everyone to bring their thinking to problems, not just their hands.

• Experience with formulation development or materials characterisation in an industrial or applied research setting.
• Familiarity with data pipeline tools, Python, or scientific computing environments (e.g. Jupyter, pandas, scikit-learn).
• Experience applying design of experiments (DoE) methodology.
• Understanding of inorganic, organic chemistry or materials science.
• Prior exposure to additive manufacturing, binder systems, or advanced materials, though this is not required; a genuine curiosity about the field matters more.

Please send your CV along with a brief portfolio note, one to two pages, or equivalent showing how you use AI tools in your work. This does not need to be a formal document. It could be a short description of a workflow you have built, a script or notebook, a problem you solved using an LLM, or a process you automated. We are interested in how you think about AI as a practical tool, not in polished presentations. The portfolio note is optional but strongly encouraged. Candidates who include one will be given priority at the shortlisting stage. What we are looking for is not impressive outputs but clear reasoning: what problem were you solving, why did you choose the approach you did, and what would you do differently?

We are not just another manufacturing company. Atomik AM is built on innovation, impact, and integrity. We challenge conventional manufacturing methods to create sustainable, high-performance solutions. If you want to be part of a team where your work makes a real difference, and you thrive in an environment where ideas turn into action, this is the place for you. We believe in fostering a diverse and inclusive workplace, where different perspectives drive better solutions. If you are ready to shape the future of advanced manufacturing, we would love to hear from you.