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Element Fleet Management

Fleet management, leasing, and technology solutions

Applied AI Lead

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeDublin, IrelandNo salary listedHybrid

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
  • At least 5 years of experience in applied artificial intelligence, machine learning, or AI-enabled product development.
  • Experience leading or mentoring technical teams.
  • Experience delivering AI solutions into production environments.
  • Experience working cross-functionally within product, engineering, and data organizations.
  • Strong communication skills and the ability to translate complex AI concepts into clear, actionable insights for non-technical stakeholders.
  • Ability to make independent decisions about AI use-case prioritization, solution design, and implementation strategies.
  • Ability to evaluate technical approaches, tools, and trade-offs in complex and evolving environments, balancing feasibility, business value, and scalability.
  • Ability to identify and apply emerging AI technologies to business problems and solve complex challenges integrating data, models, and systems.
  • Ability to balance strategic thinking with hands-on execution.

Responsibilities

  • Identify high-value AI use cases by partnering with business functions to understand operating priorities and pain points.
  • Develop and maintain a prioritized Applied AI roadmap aligned with Continuous Improvement objectives, business strategy, and enterprise priorities, delivering measurable operational and financial outcomes.
  • Evaluate emerging AI technologies and approaches to inform strategic direction and operating model.
  • Lead the design, development, and deployment of AI-powered product features and internal solutions, ensuring scalability, reliability, and alignment with user needs.
  • Oversee the translation of machine learning models, data pipelines, and AI workflows into production-ready applications in collaboration with functional leads and teams.
  • Ensure solutions follow best practices in performance, monitoring, and responsible AI usage.
  • Lead and coach team members on identifying, developing, and applying AI-powered solutions.
  • Provide technical guidance and foster a collaborative, innovative, growth-oriented environment.
  • Partner with functional leads and their teams to align priorities, dependencies, and delivery timelines.
  • Drive alignment and adoption of AI solutions across impacted business functions.
  • Establish and promote best practices for experimentation, model evaluation, and lifecycle management, including monitoring, retraining, and performance optimization.
  • Contribute to responsible AI practices, including transparency, risk awareness, and appropriate use of data.
  • Continuously identify opportunities to improve processes, tools, and frameworks supporting applied AI delivery.
  • Identify and deliver AI-driven solutions that improve efficiency, decision-making, risk management effectiveness, and the business operating model.

Desired Qualifications

  • Experience in the finance industry.

About the Company

Element Fleet Management

Fleet management, leasing, and technology solutions

Element Fleet Management provides tailored fleet solutions for businesses and government entities to manage and optimize automotive fleets. Its services cover cost management, driver productivity, vehicle uptime, fleet electrification, and technology solutions, along with leasing options. The offering combines advisory services, data-driven insights, and flexible financing to help clients decide between leasing and purchasing vehicles. The company earns revenue through service fees, leasing agreements, and technology solutions, creating multiple income streams. It differentiates itself through a strong emphasis on sustainability and supplier diversity, transparent reporting, and actionable data that clients can use to make informed decisions. The goal is to help clients reduce costs, improve fleet uptime, and transition to sustainable fleets while delivering reliable service across industries from logistics to corporate and government fleets.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1946

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