Lead Data Engineer

I am partnering with an AI Driven fast-moving company using generative AI to design breakthrough materials and chemical processes that help decarbonize heavy industry. By combining cutting-edge machine learning with experimental science, they are building the tools to reinvent how the world makes energy, fertilizer, and more—cleaner, faster, and smarter.

After a significant round of funding, they are looking to expand the team with senior hires in different areas of the business.

Lead Data Engineer

Responsibilities

• Lead and execute the internal data strategy across the organization, aligning with AI and scientific objectives.
• Design and manage data pipelines for ingestion, processing, and transformation of diverse datasets (LLMs, physical-chemical, experimental, graph data, etc.).
• Lead the deployment of machine learning models in a scalable, secure cloud environment (e.g., AWS, GCP, or Azure).
• Structure and maintain internal databases/platforms to optimize for performance and usability by AI systems, researchers, and engineers.
• Develop robust tools for querying and accessing data, enabling self-service and automation across teams.
• Collaborate closely with a multidisciplinary team of scientists, machine learning experts, and software engineers to accelerate R&D.
• Architect how data is hosted, versioned, and accessed, ensuring integrity, scalability, and reproducibility.
• Take full ownership of your projects—from design to implementation to ongoing maintenance and improvements.

Requirements

• 5+ years of industry experience in data engineering, ML infrastructure, or DevOps roles.
• Proven DevOps / infrastructure experience, including CI/CD, containerization (Docker, Kubernetes), and automation workflows.
• Experience with at least two major cloud providers (e.g., AWS, GCP, Azure).
• Strong familiarity with multi-modal data, including graph structures, natural language, lab/experimental data, and imaging formats.
• A research mindset with the ability to translate emerging academic and open-source developments into production-ready systems.
• Deep curiosity and ability to stay current with advances in machine learning, data infrastructure, and scientific computing.
• A genuine interest in environmental and sustainability challenges, and a desire to work on meaningful solutions with real-world impact.
• Strong programming skills (e.g., Python, Bash) and experience with modern data and ML tooling (e.g., Airflow, DVC, MLflow, Spark).

Following your application Jay Robins, a specialist AI Recruitment consultant will discuss the opportunity with you in detail. He will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available. This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.

Please click ‘apply’ or contact Jay Robins for any further information.

Email: jrobins@barringtonjames.com