Machine Learning Engineer - Engineering Early Talent Leadership Development Program

Eaton, a global energy management leader with nearly $25 billion in revenue in 2024, is dedicated to making energy safer, more efficient, and sustainable. With 92,000 employees serving customers in over 175 countries, we are committed to improving quality of life and protecting the environment.

Eaton’s Engineering & Technology Early Talent Leadership Development Program offers a unique opportunity to kick-start your international career. You'll receive leadership training, personal coaching, and network with senior leaders. Through rotational assignments across various locations and business areas, you will develop a broad skill set and prepare for future leadership roles.

What You’ll Do

The program will start with the role of Machine Learning (ML) Engineer in Dublin, Ireland, in the Centre for Intelligent Power (CIP) at Eaton House, which serves as Eaton's global headquarters. The CIP is a core part of Eaton’s digital journey and focuses on developing data solutions using Artificial Intelligence (AI) and Machine Learning (ML) technologies and systems. You would rotate between 2 of our teams, spending 6 months in each:

• Data Science rotation: you will learn to develop and deploy data science and analytics solutions across Eaton’s product portfolio, ensuring that our products are equipped with the latest technological advancements. You will use an understanding of our business problems to analyse data to build and release statistical, AI, and machine learning models, contributing to the ongoing development of Eaton’s Brightlayer Analytics platform. You will also be involved in designing, developing, and testing edge and cloud-based systems, ensuring they meet our high standards of performance and reliability.
• Data Engineering rotation: you will help build data driven solutions that Eaton businesses deploy in their cloud and edge environments. You will learn and apply expertise in data engineering, software engineering, MLOps, ML engineering, DevOps and QA. You will learn about deploying and scaling ML in cloud environments using containerisation and orchestration technologies. In addition, you will learn about the challenges in deploying data driven solutions in resource constrained edge environments
  
  
  

The second year of the program will take place in another EMEA country within one of the following disciplines: mechanical engineering, aerospace engineering, embedded systems, power electronics, product development, software engineering. Potential locations for the second-year assignment include Czech Republic, Germany, Italy, Austria.

Qualifications

• Currently possesses, or will have obtained a bachelor’s degree in a STEM field with a graduation date no later than August 2025. A master's degree is a plus.
• 1-3 years of professional experience (including any internships), experience in a software / data engineering / data science area is a plus
  
  
  

Skills

• Effective communication
• Proactivity and curiosity
• Ability to learn fast and take challenging tasks
• Desire to build a leadership career in a multinational company
• Flexibility to relocate within the EMEA region during the program
  
  
  

We Offer

• Being part of a company that has been in business for more than 100 years, is well known in the industry, and has a major impact on the energy industry.
• Work in a company with commitment to Inclusion & Diversity and Sustainability.
• Comprehensive support throughout the relocation process, both during and after the program, tailored to your rotation.
• Exclusive learning curriculum designed to bolster your leadership skills. During the program, you will attend 20 training sessions focused on developing key skills, such as critical thinking, emotional intelligence, career management and self-presentation.
• Annual Early Talent Conference and other events to expand your network within Eaton by connecting with senior leaders and fellow participants on key topics – from sustainability and diversity to team management and business development.
• Strong, agile, and diverse team locally and globally.
• Hybrid worktime model for balancing your work and life.
  
  
  

We are committed to ensuring equal employment opportunities for job applicants and employees. Our recruitment processes use balanced selection criteria and avoid unlawful discrimination against applicants on the basis of their age, colour, disability, marital status, national origin, gender, gender identity, genetic information, race or racial origin, religion, sexual orientation or any other status protected or required by law.

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