Senior Machine Learning Engineer

Fruition Group Ireland; Dublin; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

On-site in Dublin

Job summary

Fruition Group Ireland is seeking a talented ML Engineer to design and implement forecasting solutions for our advanced platform serving the food processing sector. This is a full-time, in-office role in Dublin city centre with regular travel to the EU and US.

You will collaborate with supply chain and leadership teams across Europe and the US, develop time-series forecasting models, and deploy production-ready solutions using Python and ML frameworks.

Qualifications

• Bachelor's or Master's degree in CS/DS/ML or related field.
• Proven experience designing, building, deploying ML models with time-series forecasting.
• Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow).

Responsibilities

• Design and implement ML forecasting solutions to predict supply and demand.
• Partner with cross-regional teams across Europe and US to understand processes.
• Develop and enhance forecasting models for agriculture and food sectors.
• Source datasets to improve model accuracy and performance.
• Communicate insights to technical and non-technical stakeholders.

Skills

Python

Time-series forecasting

Data analysis

Communication skills

Model deployment

MLOps

Education

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Engineering, or related field

Tools

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Job description

Our client is a well-capitalised, high-growth technology company building an advanced forecasting platform for the food processing sector.

This position is a full time, IN-OFFICE position in Dublin city centre, With Travel to the EU & US regularly.

The Role

Design and implement machine learning solutions that forecast supply and demand, turning complex business data into accurate predictions and embedding AI directly into day-to-day operations.

Key Responsibilities

• Partner with client supply chain, planning, and leadership teams across Europe and the US, including regular on-site engagements, to understand business processes and transform data into high-quality forecasting inputs.
• Design, develop, and continuously enhance machine learning forecasting models across a diverse portfolio of products, with a primary focus on the agriculture and food sectors.
• Identify, source, and maintain high-quality open-source and proprietary datasets to improve model accuracy and performance.
• Analyse forecasting results and communicate technical insights and business recommendations clearly to both technical and non-technical stakeholders.
• Collaborate closely with cross-functional teams to ensure forecasting solutions are effectively integrated into client operations and drive measurable business outcomes.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Engineering, or a related field.
• Proven experience designing, building, and deploying machine learning models, with strong expertise in time-series forecasting and tabular data.
• Proficiency in Python and modern machine learning frameworks and libraries (e.g. Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow).
• Ability to work with large, complex, and imperfect enterprise datasets, transforming raw data into reliable forecasting solutions.
• Experience rapidly prototyping, testing, and deploying production-ready models with a practical, results-driven approach.
• Strong understanding of manufacturing, supply chain, inventory management, or Sales & Operations Planning (S&OP), with experience in demand forecasting considered highly advantageous.
• Familiarity with MLOps, model deployment, monitoring, observability, and model interpretability techniques is desirable.
• Excellent analytical, problem-solving, and communication skills, with the ability to translate technical concepts into clear business insights for clients and stakeholders.
• Previous experience in a fast-paced startup or scale-up environment, or participation in competitive machine learning platforms would be an advantage.