Summary
Andersen is hiring an ML Engineer in Abu Dhabi to develop AI models for automated requirements engineering and a predictive supply chain platform for risk scoring and demand forecasting.
The customer is an organization operating in the technology and consulting domain, supporting businesses with the implementation of digital initiatives and process improvements. The company delivers a range of services related to software solutions, system enhancements, and advisory support, helping clients adapt to evolving technological landscapes through flexible engagement approaches and scalable delivery models.
The project is focused on developing and deploying advanced AI models for two key initiatives: automated requirements engineering using LLMs and a predictive supply chain platform for risk scoring and demand forecasting. The goal is to ensure robust, explainable, and secure models that operate within defense-grade environments.
Responsibilities
- Designing and fine-tuning LLM pipelines to interpret complex regulatory texts (e.g., military standards, building codes) and extract structured rules.
- Converting natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by downstream compliance engines.
- Implementing RAG (Retrieval-Augmented Generation) architectures to enable semantic querying of technical documentation and historical project data.
- Optimizing prompt strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining.
- Developing time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals.
- Building classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors.
- Designing algorithms for multi-objective optimization (e.g., balancing cost vs. lead time vs. risk) to support procurement decision-making.
- Containerizing models using Docker/Kubernetes and deploying them into secure, on-premise inference environments.
- Building automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability.
- Optimizing model inference latency and resource usage (e.g., quantization, distillation) to run efficiently on available hardware.
- Implementing monitoring systems to track model drift and performance in production, establishing feedback loops for continuous improvement.
Requirements
- Experience in Machine Learning Engineering for 5+ years, with a proven track record of deploying models into production environments.
- Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy).
- Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain).
- Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow).
- Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data.
- Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations.
- Ability to quickly learn and apply ML techniques to specialized domains like defense engineering, supply chain, or construction.
- Experience working in agile environments while adhering to rigorous engineering standards and documentation requirements.
- Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.
- Level of English – from Upper-Intermediate and above.
Reasons to join us
- Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..
- The opportunity to change the project and/or develop expertise in an interesting business domain.
- Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
- The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
- Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
- Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
- Certification compensation (AWS, PMP, etc).
- Referral program.
- English courses.
- Private health insurance and compensation for sports activities.
Join us!
Locations
The United Arab Emirates