We are looking for a Junior to Mid-Level Machine Learning Engineer to join a growing team in Dublin.
This is a hands-on role where you will build and improve machine learning solutions focused on supply and demand forecasting, working with real-world data to produce accurate predictions and practical business insights.
Key Responsibilities
- Build, test and improve machine learning models for supply and demand forecasting.
- Work primarily with time-series and tabular datasets.
- Clean, prepare and analyse large and sometimes imperfect datasets.
- Identify and integrate additional datasets that can improve forecasting accuracy.
- Analyse model performance and identify opportunities for improvement.
- Communicate technical findings clearly to technical and non-technical stakeholders.
- Work closely with the wider team to integrate forecasting models into production.
- Develop your knowledge of model deployment, monitoring and MLOps.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Engineering or a related field.
- Around 1–3 years' experience in Machine Learning, Data Science or a similar role. Strong graduates with relevant projects or internships may also be considered.
- Good Python skills and experience with libraries such as Pandas, NumPy and Scikit-learn.
- Practical understanding of machine learning and predictive modelling.
- Exposure to time-series forecasting through commercial experience, academic research, internships or personal projects.
- Comfortable working with and analysing large datasets.
- Good understanding of statistics and machine learning fundamentals.
- Strong analytical and problem-solving skills.
- Ability to communicate technical concepts clearly.
- Comfortable working in a fast-paced environment.
Experience in any of the following would be beneficial but is not essential:
- Demand or supply forecasting
- Manufacturing, food, agriculture or supply chain data
- Inventory planning or S&OP
- PyTorch or TensorFlow
- MLOps and model deployment
- Cloud platforms
- machine learning projects