Machine Learning Product Manager

Role overview

This opportunity is being advertised for a partner employer that will handle applications and the rest of the hiring process. The company is seeking a Machine Learning Product Manager in Ireland to shape and improve intelligent decision-making products that deliver clear business value.

In this position, you will work across product, data science, engineering, analytics, commercial, and leadership teams to turn complex business problems into scalable AI-driven solutions. The role calls for strong product leadership, comfort with technical detail, and the ability to make data-backed decisions in environments with a fair amount of ambiguity.

You will help define how automated systems support growth, boost efficiency, and combine machine intelligence with human oversight in a practical and responsible way. This is well suited to someone who enjoys strategic problem-solving, experimentation, and influencing key business outcomes through technology.

Core accountabilities

• Set the product direction, long-term plan, and roadmap for machine learning-based decisioning and optimization capabilities.
• Convert business goals into product requirements, user stories, decision rules, and measurable success indicators.
• Work closely with Data Science, Engineering, Analytics, Commercial, and Leadership stakeholders to build systems that support growth and operational performance.
• Spot, assess, and rank high-value opportunities where machine learning and automation can improve outcomes.
• Run discovery work to map current processes, identify operational pain points, and uncover ways to improve them with AI-led solutions.
• Coordinate with technical teams on data needs, model goals, testing frameworks, monitoring plans, and feedback loops.
• Create human-in-the-loop workflows that combine automation with visibility, control, and dependable execution.
• Lead experimentation and validation efforts to measure model quality, reduce risk, and guide product choices with evidence.
• Define, track, and improve product and machine learning metrics so the business impact remains clear and measurable.
• Explain technical ideas, ML systems, and optimization approaches clearly to both technical and non-technical audiences.

Requirements

• At least 5 years in product management, including multiple years in machine learning, artificial intelligence, predictive systems, or algorithmic decision products.
• Background working with Data Science and Engineering teams to deliver ML-enabled products and translate business needs into technical solutions.
• Strong analytical approach, with hands-on experience in experimentation, hypothesis testing, performance tracking, and evidence-based decision-making.
• Ability to weigh complex commercial and business trade-offs while balancing customer, operational, and organizational priorities.
• Good technical understanding of data pipelines, model development lifecycles, model evaluation methods, system limitations, and experimentation techniques.
• Experience operating in strategic, cross-functional, and ambiguous product settings that require discovery and iteration.
• Strong stakeholder management and relationship-building skills, with the ability to align different teams around shared goals.
• Structured, results-focused approach to discovery, roadmap planning, prioritization, and delivery.
• Excellent communication skills and the ability to simplify complex systems for different audiences.
• Experience in marketplaces, recommendation engines, ranking systems, pricing platforms, advertising technology, or similar optimization-heavy areas is preferred.
• Interest in artificial intelligence, intelligent systems, sustainability, and building measurable business value through technology.

Benefits and working style

• Fully remote arrangement with the flexibility to work from eligible European locations.
• Flexible hours and significant autonomy in organizing your work and schedule.
• A dedicated learning and development budget for courses, certifications, conferences, and training.
• Access to coaching, personal development support, and mental health resources.
• Regular internal workshops, knowledge-sharing sessions, and cross-functional learning opportunities.
• Opportunities to join company-wide meetups, team-building activities, workshops, and collaborative office weeks during the year.
• An inclusive, feedback-led culture that supports innovation, experimentation, and ongoing improvement.
• A collaborative international team with a strong focus on ownership and impact.
• Optional use of modern office spaces for in-person collaboration and networking.
• Strong emphasis on work-life balance and employee well-being.

Application and privacy information

The application process is managed by the partner hiring company. Applications are reviewed using an AI-assisted matching process to identify candidates who best fit the role’s core requirements, and the resulting shortlist is shared with the employer. Final hiring decisions, interviews, and assessments are handled by the employer’s internal team.

Submitting an application means your personal data may be processed to assess candidacy and shared with the hiring employer in line with applicable data protection rules, including GDPR. You may request access, correction, deletion, or objection regarding your data where applicable.

AI tools may be used to support parts of the hiring workflow, such as reviewing applications, analyzing resumes, or checking responses for potential inconsistencies or verification signals. These tools assist the recruitment process but do not replace human judgment, and final decisions are made by people.