AI Engineer (LLM and Machine Learning) - Materials Informatics Platform

We are searching for an experienced AI Engineer to contribute to our machine learning and AI capabilities within the AI engineering team. This role is central to our mission, offering the opportunity to shape the future of materials science and engineering through AI. The ideal candidate will possess a deep understanding and experience with AI/ML technologies, exceptional problem-solving skills, and a passion for innovation.

Responsibilities

• Play a key role in the AI engineering team, which is responsible for the development and enhancement of our AI-driven prediction and optimization tools.
• Research and develop applications of Large Language Models (LLMs) to be incorporated into our platform.
• Craft and maintain state-of-the-art AI models, with an emphasis on reliability and scalability in production environments.
• Engage in data preparation, algorithm selection, model tuning, and pipeline construction to support diverse R&D projects.
• Collaborate closely with cross-functional teams to identify opportunities for AI integration and improvement.
• Stay up-to-date with new technologies and methodologies in AI, continuously seeking ways to improve our platform and processes.

Requirements

• Proven industry experience in AI/ML engineering (4+ years).
• 1-2 years of experience in developing and productizing LLM applications, with hands-on expertise in tools and techniques such as Hugging Face, vector databases, LlamaIndex, fine-tuning LLMs, retrieval-augmented generation (RAG), and LLM benchmarking and validation.
• Extensive experience with data preparation, ML algorithm selection, model tuning, and building robust pipelines using tools like MLflow and Kubeflow.
• Proficiency in Python (4+ years) and adherence to high-quality coding practices.
• Demonstrable experience with production-level code deployment.
• Experience working in a cloud environment, with a preference for GCP.
• Excellent communication, with the ability to both listen and teach effectively.
• A curious and innovative mindset, constantly exploring new technologies and methodologies.

Advantages

• Knowledge of Bayesian optimization and its applications.
• Experience in chemistry, materials science or related fields.

What We Offer

• A dynamic and supportive environment where your work directly impacts the future of materials science and engineering.
• The opportunity to work with a team of passionate, like-minded professionals.
• Hybrid work setup, combining the connectivity of in-office collaboration with the flexibility of remote work two days a week.
• Professional development and continuous learning opportunities.

About MaterialsZone

MaterialsZone is a pioneering Materials Informatics company, dedicated to accelerating the R&D process across diverse materials-based industries including 3D printing, batteries, photovoltaics, plastics and more. Our platform transforms the way organizations conduct their R&D processes, integrating data management, collaboration, visualization, AI-driven insights, and predictions to propel engineers toward achieving superior outcomes, faster and more efficiently.

Materials Informatics

Materials informatics is the application of data science and machine learning techniques to the field of materials science, aiming to discover new materials, optimize existing ones, and understand material properties more efficiently. It involves the collection, analysis, and modeling of large datasets relating to material compositions, structures, and properties to predict outcomes and accelerate material innovation. By leveraging computational tools, materials informatics enables the identification of patterns and relationships within data that are not readily apparent, significantly reducing the time and cost associated with traditional experimental approaches in material discovery and development.