ML Engineer – Generative AI

About Us

We are the independent expert in assurance and risk management. Driven by our purpose, to safeguard life, property and the environment, we empower our customers and their stakeholders with facts and reliable insights so that critical decisions can be made with confidence.

We help customers navigate the complex transition to a decarbonised and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments navigate the many complex, inter‑related transitions taking place globally and regionally, in the energy industry.

Green Power Monitor , a DNV company, is at the heart of the global energy transformation. We use data‑driven digital solutions to optimise the performance of renewable energy installations around the world. Our work contributes to a more diverse, more sustainable global energy mix.

We are looking for an ML Engineer to help create, productise and evolve generative AI solutions on Horizon, Green Power Monitor ’s cloud platform that transforms renewable energy operational data into actionable insights for monitoring, optimisation and decision‑making.

This is a hands‑on, impact‑driven role where you will build LLM‑powered agents and embed them directly into a production system used by renewable energy professionals worldwide. You will work closely with product managers and software engineers to design, deploy and maintain production‑grade AI systems, starting with a user‑oriented AI assistant embedded in Horizon.

Over the course of the year, your work will support the strategic goal of enriching Horizon with LLM models, starting with a predictive maintenance module and evolving the platform to become more autonomous and intelligent for users, turning operational data into actionable insights.

• Connect to diverse data sources within the Horizon platform, including operational data, structured metadata and technical documentation, and design Retrieval‑Augmented Generation (RAG) pipelines for scalable AI systems.
• Extract, transform and structure data for optimal use with LLMs, manage embeddings, indexing and context retrieval and ensure AI models are grounded in accurate, real‑world information.
• Design, deploy, fine‑tune and continuously improve production‑grade LLM and multimodal agents, optimising prompts, mitigating hallucinations and evaluating performance to deliver reliable, context‑aware outputs.
• Build and maintain client‑facing AI assistants and chatbots, explaining system behaviour, capabilities and limitations to both technical and non‑technical stakeholders, and integrating AI features seamlessly into Horizon workflows.
• Stay up to date with advances in generative AI, agent‑based systems and instruction‑tuned models, experimenting with frameworks like Lang Chain and collaborating on experiments using large instruction‑tuned models.
• Collaborate closely with product and software teams to take AI solutions from concept to production, ensuring features are robust, scalable and directly support Horizon users in monitoring, optimising and managing renewable energy assets.

You’ll take cutting‑edge LLM and agent‑based systems out of the lab and into production, building AI that directly supports the operation and optimisation of renewable energy assets at global scale.

• Great atmosphere of working together with professionals and some of the most engaged and knowledgeable people in the industry.
• Receive guidance from colleagues through coaching, mentoring and participation in international networks.
• Advance your professional skills and technical expertise through individual competence development plans and tailored training.
• Be part of a world‑growing and renowned organisation with origins dating back to 1864.
• Medical scheme, commuting allowance, life insurance, pension plan, kindergarten allowance, 40 hours per week with flexible schedule, home‑working allowance (up to 2 days per week), 23 days of annual leave, employee referral scheme.

• Master’s degree or equivalent…