Senior Machine Learning Engineer

About the Role

Our client is a financially strong, rapidly expanding tech firm developing a sophisticated forecasting platform specifically tailored for the food processing industry. This full-time position is based onsite in Dublin city centre and includes frequent travel across the EU and the US.

Key Responsibilities

• Collaborate with supply chain, planning, and leadership teams in Europe and the US, including onsite visits, to thoroughly understand business practices and convert data into reliable forecasting inputs.
• Design, develop, and continuously improve machine learning models for forecasting across a broad range of products, focusing mainly on agriculture and food sectors.
• Source and manage high-quality open-source and proprietary datasets to enhance model precision and performance.
• Analyze forecasting outcomes and convey both technical insights and practical business advice effectively to technical and non-technical audiences.
• Work with cross-disciplinary teams to integrate forecasting solutions into operations, ensuring measurable improvements in business processes.

Candidate Requirements

• A Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Engineering, or related disciplines.
• Demonstrable experience in designing, building, and deploying machine learning models, particularly focused on time-series forecasting and tabular datasets.
• Strong proficiency in Python alongside modern machine learning libraries such as Pandas, NumPy, Scikit-learn, PyTorch, and TensorFlow.
• Capability to work effectively with extensive, complex, and imperfect datasets, converting raw data into dependable forecasting solutions.
• Experience in rapid prototyping, rigorous testing, and deploying models that are production-ready, emphasizing practical and result-oriented methods.
• Good knowledge of manufacturing, supply chain management, inventory control, or Sales & Operations Planning (S&OP), especially with demand forecasting expertise.
• Familiarity with MLOps practices, including model deployment, monitoring, transparency, and interpretability techniques is beneficial.
• Excellent analytical skills, problem-solving abilities, and clear communication prowess to translate complex technical content into actionable business insights.
• Previous exposure to high-growth startup or scale-up environments or experience with competitive machine learning challenges is a plus.

Benefits

• 25 days paid annual leave
• Participation in company pension scheme
• Company-sponsored social and corporate events