Role: Machine Learning EngineerDuration: 12 months + extension (long term project)Engagement: Contract/freelance (full time, 5 days per week, 8 hour days)Location: Onsite in Cork 3-4 days per week, remaining remoteGeneral Summary: This position exists to design, develop, and deploy machine learning models and systems that solve business problems and drive data-driven decision-making across the organization. The Machine Learning Engineer builds scalable ML infrastructure and pipelines that enable the productionization of AI solutions. This role bridges the gap between data science research and operational deployment of machine learning capabilities.Duties & Responsibilities:Design, develop, and deploy machine learning models and algorithms to address business requirements and optimize operational processes 25%Build and maintain scalable ML infrastructure, including data pipelines, model training workflows, and deployment systems 20%Collaborate with data scientists, software engineers, and stakeholders to translate business problems into technical ML solutions 15%Monitor, evaluate, and improve model performance in production environments through A/B testing, retraining, and optimization 15%Implement MLOps best practices including version control, automated testing, and continuous integration/deployment for ML systems 15%Research and evaluate emerging ML technologies, frameworks, and methodologies to enhance team capabilities and solution quality 10%Knowledge, Skills and Abilities (KSAs):Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learnKnowledge of machine learning algorithms, deep learning architectures, and statistical modeling techniquesAbility to design and implement scalable data pipelines and ML infrastructure using cloud platforms (AWS, Azure, or GCP)Experience with MLOps tools and practices including model versioning, monitoring, and deployment automationStrong understanding of software engineering principles including version control, testing, and CI/CDAbility to work with large datasets and distributed computing frameworks such as Spark or DaskStrong problem-solving skills and ability to translate business requirements into technical solutionsEffective communication skills to collaborate with cross-functional teams and explain technical concepts to non-technical stakeholdersWork Experience &/or Education:Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or related technical field3+ years of experience developing and deploying machine learning models in production environmentsDemonstrated experience building ML pipelines and infrastructure at scaleProficiency with SQL and relational databases