Experteer Overview
In this role you will develop practical AI, ML, and optimization solutions to help industrial teams analyze data and support decisions. You will apply frontier models and build end-to-end AI-enabled applications that are reliable, explainable, and scalable. You’ll design knowledge graphs and data pipelines that connect process data, documents, and domain knowledge, collaborating with cross-functional teams to deliver measurable value. This is a remote role with travel, offering impact at scale in health, biosciences, and industrial domains.

Compensaciones / Beneficios
• Develop AI/ML and optimization solutions for industrial data
• Apply large language models and multimodal models for search, analysis, and decision support
• Build end-to-end AI applications with data pipelines, prompts, agents, and evaluations
• Design knowledge graphs and structured domain knowledge to connect data types and business context
• Collaborate with domain experts to translate scientific and process questions into data products and workflows
• Develop robust data pipelines for structured and unstructured data (time-series, lab, manufacturing, documents)
• Contribute to model validation, monitoring, governance, and continuous improvement
• Work with cross-functional teams to ensure solutions are useful, trustworthy, and adoptable

Responsabilidades




• Master's or PhD in Chemical Engineering, Biochemical Engineering, Bioinformatics, Process Control, Computer Science, Data Science or Applied Mathematics
• Proven industrial track record delivering measurable business impact in production or operational settings
• Hands-on Python and modern ML workflows (data prep, modeling, deployment, monitoring)
• Experience delivering end-to-end AI/ML applications in real industrial environments
• Understanding of frontier model capabilities, prompt design, retrieval augmented generation, evaluation, and human-in-the-loop workflows
• Experience with structured and unstructured data (time-series, documents, knowledge bases)
• Knowledge of optimization, process control, forecasting, anomaly detection, and other ML methods
• Software engineering practices (version control, testing, APIs, containers, CI/CD, maintainable code)
• Strong ability to communicate outputs and trade-offs to technical and non-technical audiences
• Delivery-oriented mindset with curiosity about industrial and process control problems

Requisitos principales
• remote-based work
• general collaboration
• learning and development opportunities
• exposure to diverse technical communities
• focus on meaningful, impactful projects
• stable, innovation-friendly environment

📌 AI Engineer (Benicarló)
🏢 International Flavors u0026 Fragrances
📍 Benicarló