• You will work on the backend services behind our route-planning estimator and other operational estimators (e.g., process durations, driver availability) and ensure their stability and maintainability. • You take responsibility for code quality and structure in our ML repositories (reviews, refactorings, architecture). • You work closely with our Data Scientists and reliably bring models and feature pipelines into production. • You develop and operate the associated data and training pipelines in Databricks. • You build and maintain CI/CD pipelines in Azure DevOps – including automated tests and deployments. • You ensure that our systems run reliably in the cloud environment, analyze production incidents and derive sustainable improvements for code and processes.

Role Description Are you passionate about a career in tech and genuinely interested in working for an organisation tackling online harms, from violent extremism and gender based violence to disinformation and child online exploitation? We have a rare and exciting opportunity for an AI/Machine Learning Engineer to join Moonshot, supporting the Director of Engineering. We are building our Ireland based development team from the ground up, and we're looking for an experienced individual to help with this effort and take our software to the next phase of its evolution. This role involves regular exposure to violent, extremist, and otherwise harmful content, including material related to online radicalisation and abuse, as part of dataset review, model training, and evaluation work. You are someone who: - Is passionate about producing high quality, user focussed software systems, and keeping them that way. - Understands how to use AI/ML to get insights out of large datasets. - Loves working in a high performance team and operating environment, built on mutual trust and continuous improvement. - Wants to grow their technical and non-technical skills and responsibilities in a unique organisation. - Deeply cares about using their skills to solve complex problems, using technology to disrupt online harm and protect vulnerable people. Your responsibilities will include: - Developing, training, tuning and running ML models on our data to get answers to key questions. - Integrating and maintaining these models within our software products. - Monitoring model inference outputs to assess performance degradation over time. - Establishing feedback mechanisms with end users to continuously improve model performance. - Developing and integrating new analytical algorithms to run against large datasets. - Guiding our teams on how best to utilise AI/ML in ethical, appropriate and values driven ways. Qualifications - 3-5 years of data analytical experience in a commercial environment. - Experience fine-tuning and training machine learning models, as well as integrating machine learning/AI within software products. - Working knowledge of NLP and classification techniques. - Hands-on experience with ML frameworks, such as PyTorch, Hugging Face Transformers, or scikit-learn. - Experience and understanding of model evaluation methodologies, calibration and performance metrics. - Strong working knowledge of Python. - Strong working knowledge of large scale data management, processing and analysis. - Comfortable working with various data management and storage systems, including relational (e.g. MySQL, Athena) and file based (e.g. parquet) systems. - Strong data architecture and modelling skills. - A good understanding of modern engineering practices, including DevOps, CI/CD development, and source code management. - Experience working with cloud infrastructure (AWS and GCP preferred). - Ability to learn quickly across technical and business problem spaces. - Ability to understand complex data. - Resilient and open minded in ambiguous situations, with the ability to approach challenges from multiple perspectives. - Adept at communicating complex technical concepts to non-expert audiences. - Excellent problem solving skills, with the ability to work well with cross-functional teams. - Experience working in a culture of high trust, where ideas can be freely shared and discussed, and where the team makes outcome oriented decisions together for the benefit of the mission. Requirements - We require and will check on candidates' eligibility to work in Ireland and pass any relevant security clearance procedures per the needs of clients. Desirable - Familiarity with, and passion for, ending online harms, including violent extremism, disinformation, and gender based violence. - Well versed in Scrum and/or Kanban. - Experience integrating models into data pipelines. - Comfortable with responsibility, decision making, ownership and autonomy. - Conscious of security and data protection when contributing to all aspects of software delivery. - Keeps up to date on the tools and processes you work with, and applies new things you have learned. - Experience working in a fast paced, agile environment with dynamic priorities, and knows how to balance this without affecting the reliability and robustness of your software. Benefits - 30 days' paid annual leave, excluding public holidays. - Dental and Vision package. - Private healthcare package, including coverage for partners and children. - Employee Assistance Programme providing access to mental health support. - Generous maternity and paternity leave: 26 weeks paid maternity leave, 8 weeks paid paternity leave. - All permanent employees are granted share options upon employment. - Salary: €85,000 - €90,000 per annum (depending on skills and experience).

• The role involves a strategic project focused on promotions optimization and sales forecasting across international markets. • Responsibilities include designing, developing, and operationalizing advanced predictive and analytical models to support commercial decision-making at a global scale. • The consultant will act as a senior hands-on expert, combining strong data science expertise with robust engineering skills to deliver production-ready solutions on AWS. • The role will contribute to demand forecasting, promotional effectiveness analysis, price elasticity modeling, and multi-market modeling, taking into account seasonality, market dynamics, and external demand drivers. • The position also includes implementing MLOps practices on Amazon SageMaker, model monitoring, automated retraining, documentation, and knowledge transfer, while collaborating with data teams and business stakeholders across multiple regions.

• Investigate why documents fail at population scale • Own and evolve the accuracy measurement framework • Design fixes for pipeline logic errors • Collaborate with AI team on model architecture and ML best practices • Build an embedding-based entity matching service and an OCR correction layer • Set up ML pipeline orchestration and MLOps practices