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 transform complex operational data into intelligent systems that drive automation, predictive insights, and efficiency improvements across high‑performance settings.

Key responsibilities

• Define and execute AI and optimization strategies to improve operational efficiency and measurable business performance.
• Design and maintain scalable data models, schemas, and telemetry structures supporting AI and machine‑learning initiatives.
• Develop, deploy, and optimise models for anomaly detection, predictive maintenance, automation, performance optimisation, and forecasting.
• Collaborate with engineering teams to integrate AI capabilities into existing systems, APIs, and production workflows.
• Continuously monitor and improve model performance, reliability, explainability, and scalability in live environments.
• Translate operational challenges into data‑driven solutions and actionable insights with cross‑functional stakeholders.
• Document architectures, modelling assumptions, and AI workflows while promoting a data‑driven culture.
• Stay informed on emerging trends in AI, optimisation, industrial analytics, and automation technologies.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Engineering, Statistics or a related technical field.
• Minimum 3 years of experience in AI/ML engineering, applied optimisation, data science or related analytical roles.
• Strong expertise in Python and modern machine‑learning frameworks such as PyTorch, TensorFlow or Scikit‑Learn.
• Proficiency in JavaScript or TypeScript within Node.js environments.
• Experience designing and managing large‑scale, time‑series‑focused data architectures and pipelines.
• Solid understanding of optimisation techniques, predictive modelling, anomaly detection and telemetry‑based AI systems.
• Familiarity with Docker and containerised deployment environments.
• Experience deploying, monitoring and maintaining production AI systems.

Required skills

• Python
• PyTorch
• TensorFlow
• Scikit‑Learn
• JavaScript
• TypeScript
• Node.js
• Time‑series data architectures
• Docker