Company Description EntroMetrix builds a physics-informed intelligence layer that helps industrial organizations reduce operational complexity and continuously optimize production, energy use, and materials. By fusing advanced analytics with real-world physics, EntroMetrix enables smarter, more efficient decision-making at scale. The company’s solutions are designed to unlock a new standard of industrial performance, driving measurable gains in productivity, sustainability, and resilience. Applicants can expect to work in a technically rigorous environment focused on real-world impact and continuous improvement.
Role Description This is a full-time, on-site role based in the London Area, United Kingdom, for a Full Stack Developer, AI Deployment. You will design, build, and maintain end-to-end web applications that integrate AI models into production-ready systems, including APIs, services, and user interfaces. Day-to-day responsibilities include developing secure and scalable backend services, implementing responsive front-end components, and connecting data pipelines to model-serving infrastructure. You will collaborate closely with data scientists, ML engineers, and product stakeholders to translate model outputs into intuitive tools and dashboards for industrial users. The role also involves writing clean, testable code, conducting code reviews, troubleshooting production issues, and contributing to deployment automation and performance optimization.
Qualifications

• Strong software engineering foundation, with experience in Software Development and Full-Stack Development for production systems.
• Proficiency in Back-End Web Development, including RESTful APIs, microservices, and integration with data and model-serving layers.
• Hands-on Front-End Development experience using modern frameworks (e.g., React, Vue, or Angular) and responsive UI design.
• Solid understanding of web presentation technologies, including Cascading Style Sheets (CSS), HTML, and related tooling.
• Experience deploying or integrating AI/ML models into applications (e.g., via APIs, model servers, or cloud-based ML platforms).
• Familiarity with cloud platforms (such as AWS, Azure, or GCP), containerization (Docker), and CI/CD pipelines.
• Strong problem-solving skills, attention to detail, and ability to work effectively with cross-functional teams in a fast-paced environment.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.