At a Glance
- Tasks: Develop and deploy AI/ML models for innovative energy solutions.
- Company: GE Vernova is leading the charge towards sustainable energy and smart infrastructure.
- Benefits: Enjoy flexible work arrangements, competitive benefits, and opportunities for personal growth.
- Other info: Collaborate on cutting-edge projects that shape the future of energy.
- Why this job: Join a dynamic team making a real impact in the energy transition and innovation.
- Qualifications: Masters or PhD in relevant fields with experience in AI/ML and energy sectors required.
The predicted salary is between 36000 - 60000 £ per year.
GE Vernova is accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life. Are you excited at the opportunity to electrify and decarbonize the world? We are looking for a passionate, creative, and results-oriented Machine Learning (ML) Engineer with substantial experience in the energy, smart infrastructure, or industrial automation sectors to join our AI & Grid Innovation team. In this role, you will be at the forefront of developing, deploying, and validating cutting-edge AI/ML models designed specifically for grid innovation applications. You will play a key role in building systems to test and verify proof-of-concepts, delivering AI-driven solutions both at the edge and in the cloud.
Reporting to the AI Director within the CTO organization, this position offers the opportunity to work collaboratively with Grid Automation product lines, R&D teams, and other business units to create impactful, sustainable, and inclusive solutions across energy systems, smart infrastructure, and industrial automation. Your expertise in automation, AI, and their integration into these domains will be essential in shaping the company’s mission to foster innovation, inclusivity, and progress.
Essential Responsibilities
- Lead the design, development, and deployment of scalable AI/ML models for grid innovation applications in the energy, smart infrastructure, or industrial automation sectors.
- Create innovative analytics to optimize grid system performance and product differentiation.
- Develop AI/ML applications for customer-driven use cases, including predictive maintenance and load forecasting.
- Validate and verify AI/ML proof-of-concepts in real-world environments, ensuring they meet the diverse needs of our customers.
- Monitor, maintain, and optimize deployed AI/ML models to continuously enhance their accuracy and performance.
- Manage the collection, structuring, and analysis of data to enable seamless AI/ML applications.
- Ensure that models are production-ready and continuously improve in line with emerging needs and technologies.
- Embrace MLOps principles to streamline the deployment and updating of ML models in production.
- Collaborate closely with cross-functional teams to identify business challenges and deliver AI-driven solutions that are efficient, equitable, and scalable.
- Integrate AI/ML solutions effortlessly into grid automation systems, whether in the cloud or at the edge.
Must-Have Requirements
- Masters or PhD in Computer Science, Information Technology, Electrical Engineering, or a related field.
- Proven experience in the energy, smart infrastructure, or industrial automation sectors, with expertise in system protection, automation, monitoring, and diagnostics.
- Strong foundation in AI/ML techniques, including supervised, unsupervised, and reinforcement learning, deep learning, and large language models (LLMs).
- Experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Hands-on experience deploying ML models in production environments using MLOps principles.
- Expertise in relevant AI/ML applications, such as predictive maintenance, load forecasting, or optimization.
- Proficiency in programming languages such as Python, R, MATLAB, or C++.
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) and microservices architecture.
Nice-to-Have Requirements
- Experience with data modeling, containerization (Docker, Kubernetes), and distributed computing (Spark, Scala).
- Familiarity with GraphDB, MongoDB, SQL/NoSQL, and other DBMS technologies.
- Understanding of system automation, protection, and diagnostics in relevant sectors.
- Experience with deep learning algorithms, reinforcement learning, NLP, and computer vision in applicable domains.
- Excellent communication, organizational, and problem-solving skills, with a strong emphasis on teamwork, collaboration, and fostering inclusive environments.
At GE Vernova - Grid Automation, you will have the opportunity to work on cutting-edge projects that shape the future of energy. We offer a collaborative environment where your expertise will be valued, and your contributions will make a tangible impact. Join us and be part of a team that is driving innovation and excellence in control systems.
About GEV Grid Solutions
At GEV Grid Solutions we are electrifying the world with advanced grid technologies. As leaders in the energy space our goal is to accelerate the transition for a more energy efficient grid to fulfil the needs of tomorrow. With a focus on growth and sustainability GE Grid Solutions plays a pivotal role in integrating Renewables onto the grid to drive to carbon neutral. In Grid Solutions we help enable the transition for a greener more reliable Grid. GE Grid Solutions has the most advanced and comprehensive product and solutions portfolio within the energy sector.
Why We Come To Work
At GEV, our engineers are always up for the challenge - and we’re always driven to find the best solution. Our projects are unique and interesting, and you’ll need to bring a solution-focused, positive approach to each one to do your best. Surrounded by committed, loyal colleagues, if you can dare to bring your ingenuity and desire to make an impact, you’ll be exposed to game-changing, diverse projects that truly allow you to play your part in the energy transition.
What We Offer
A key role in a dynamic, international working environment with a large degree of flexibility of work agreements. Competitive benefits, and great development opportunities - including private health insurance.
Machine Learning Engineer – AI for Grid Innovation & Energy Transition employer: GE Vernova
At GE Vernova, we are committed to fostering a collaborative and innovative work culture that empowers our employees to make a meaningful impact in the energy sector. As a Machine Learning Engineer, you will have access to competitive benefits, including private health insurance, and ample opportunities for professional growth within a dynamic international environment. Join us in shaping the future of energy while working on cutting-edge projects that drive sustainability and inclusivity.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer – AI for Grid Innovation & Energy Transition
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning, especially as they relate to energy systems. Understanding how these technologies are being applied in grid innovation will help you speak confidently about your ideas during interviews.
✨Tip Number 2
Network with professionals in the energy and automation sectors. Attend industry conferences or webinars where you can meet potential colleagues and learn more about the challenges they face, which can give you insights to discuss in your application.
✨Tip Number 3
Showcase your hands-on experience with MLOps principles. Be prepared to discuss specific projects where you've deployed ML models in production environments, as this practical knowledge is highly valued for the role.
✨Tip Number 4
Research GE Vernova's recent projects and initiatives in grid solutions. Being knowledgeable about their work will not only impress during interviews but also help you align your skills and experiences with their goals.
We think you need these skills to ace Machine Learning Engineer – AI for Grid Innovation & Energy Transition
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning, AI, and the energy sector. Use specific examples of projects you've worked on that align with the job description, such as predictive maintenance or load forecasting.
Craft a Compelling Cover Letter:In your cover letter, express your passion for energy transition and how your skills can contribute to GE Vernova's mission. Mention any innovative projects you've led or participated in, and how they relate to grid innovation.
Showcase Technical Skills:Clearly list your technical skills, especially those mentioned in the job description, like proficiency in Python, experience with ML frameworks, and familiarity with cloud platforms. Provide context for how you've applied these skills in real-world scenarios.
Highlight Collaboration Experience:Since the role involves working with cross-functional teams, include examples of past collaborations. Discuss how you contributed to team success and how you fostered an inclusive environment in your previous roles.
How to prepare for a job interview at GE Vernova
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI/ML techniques and frameworks like TensorFlow or PyTorch. Bring examples of projects where you've successfully deployed models in production, as this will demonstrate your hands-on expertise.
✨Understand the Energy Sector
Familiarise yourself with current trends and challenges in the energy, smart infrastructure, and industrial automation sectors. Being able to discuss how your skills can contribute to grid innovation will set you apart from other candidates.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Think about past experiences where you tackled complex issues, particularly in AI/ML applications, and be ready to explain your thought process.
✨Emphasise Collaboration and Communication
Since the role involves working closely with cross-functional teams, highlight your teamwork and communication skills. Share examples of how you've collaborated on projects and contributed to a positive team environment.
