Senior Machine Learning Engineer

Headquartered in Abu Dhabi, UAE, specializes in developing AI-driven solutions for defense engineering and supply chain optimization by designing and deploying advanced machine learning models that enhance regulatory compliance, risk prediction, and operational forecasting. The company focuses on integrating generative AI and predictive analytics to automate complex requirements parsing and optimize procurement and logistics efficiencies within security-constrained environments.

We are seeking a Senior Machine Learning Engineer to lead the development and deployment of cutting‑edge AI models for our Intelligent Supply Chain and platform initiatives. In this pivotal role, you will oversee the entire lifecycle of machine learning systems—from architectural design and data preprocessing to model training, optimization, and secure production deployment. Your work will bridge generative AI and traditional machine learning, driving innovation in two key areas: the platform, which automates requirements engineering through advanced LLMs, and Intelligent Supply Chain, which delivers predictive risk scoring and demand forecasting.

Operating within a structured 'Sprint Zero' to 'Stage Gate' delivery framework, you will ensure that our models are not only highly accurate but also robust, explainable, and deployable within stringent defense‑grade security environments. This role demands expertise in both technical execution and cross‑functional collaboration, as you will work closely with domain experts, data scientists, and backend engineers to translate complex business challenges into scalable AI solutions.

Your contributions will directly impact critical national infrastructure, shaping the resilience of supply chains and the design of defense systems through advanced machine learning applications.

• Lead the design and implementation of Large Language Model (LLM) pipelines for automated requirements engineering, focusing on parsing complex regulatory texts such as military standards and building codes to extract structured rules.
• Convert natural language requirements into executable logic tuples and formalized formats for downstream compliance engines, ensuring seamless integration with technical workflows.
• Develop Retrieval‑Augmented Generation (RAG) architectures to enable semantic search capabilities across technical documentation and historical project data, enhancing query precision and retrieval efficiency.
• Optimize prompt engineering strategies, including few‑shot learning and chain‑of‑thought techniques, to improve model performance on domain‑specific tasks without requiring extensive retraining.
• Design and deploy time‑series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals for accurate supply chain planning.
• Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors, ensuring robust risk mitigation strategies.
• Create multi‑objective optimization algorithms to balance critical procurement factors such as cost, lead time, and risk, directly supporting data‑driven decision‑making in supply chain operations.
• Containerize machine learning models using Docker and Kubernetes, deploying them into secure, on‑premise inference environments that meet defense‑grade security standards.
• Construct automated training and inference pipelines using Kubeflow or MLflow to ensure reproducibility, scalability, and seamless integration with existing MLOps workflows.
• Optimize model inference latency and resource usage through techniques such as quantization and distillation, ensuring efficient performance across available hardware configurations.
• Implement comprehensive monitoring systems to track model drift and performance degradation in production, establishing feedback loops for continuous improvement and retraining.

• 5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments.
• Expert proficiency in Python and standard ML…