AI & Optimization Engineer

About the role

This position offers the chance to work at the intersection of artificial intelligence, optimization, and large‑scale infrastructure operations in a fully remote, globally distributed environment. You will turn complex operational data into intelligent systems that drive automation, predictive insights, and efficiency improvements.

Key responsibilities

• Define and execute AI and optimization strategies to improve operational efficiency and business performance.
• Design and maintain scalable data models, schemas, and telemetry structures for AI initiatives.
• Develop, deploy, and optimise machine‑learning models for anomaly detection, predictive maintenance, automation, and forecasting.
• Integrate AI capabilities into existing systems, APIs, and production workflows.
• Monitor model performance, reliability, explainability, and scalability in live settings.
• Collaborate with cross‑functional stakeholders to translate operational challenges into data‑driven solutions.
• Document architectures, modelling assumptions, and AI workflows while fostering a data‑driven culture.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Engineering, Statistics or a related field.
• Minimum 3 years of experience in AI/ML engineering, applied optimisation, or data‑science roles.
• Strong expertise in Python and modern ML frameworks.
• Proficiency in JavaScript or TypeScript within Node.js environments.
• Experience with large‑scale, time‑series data architectures and pipelines.
• Solid understanding of optimisation techniques, predictive modelling, and anomaly detection.
• Familiarity with Docker and containerised deployment.

Required skills

• Python
• PyTorch
• TensorFlow
• Scikit‑Learn
• JavaScript
• TypeScript
• Node.js
• Docker
• Time‑series data pipelines
• Optimization techniques
• Predictive modelling
• Anomaly detection