Digital Twin Engineer

Gradyent — Netherlands · Posted ~21 hours ago

Full-time

Skills

digital twins data-driven solutions energy systems data science physics-based modeling AI geospatial data sensor data real-time systems digital twin platforms physics-based models

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Summary ✨ AI‑Generated

A Digital Twin Engineer is sought to develop data-driven models of complex energy infrastructure. You will combine real-time sensor and geographic data with physics-based models and AI to optimize operations, improve decision-making, and simulate future scenarios.

Highlights

Work on advanced digital twin technology that combines real-time data, physical models, AI, weather, and geographic information to optimize complex energy infrastructure. The role sits at the intersection of engineering, data science, and energy systems.

Description

About Gradyent Providing heating and cooling for homes, buildings, and industry accounts for nearly 50% of global final energy consumption. As these systems become increasingly interconnected with multiple energy carriers, their complexity will grow significantly. Traditional software is no longer sufficient to manage this level of complexity. This increases the need for digital and data-driven solutions to improve efficiency, enable smarter decision-making, and ensure reliable energy delivery. With our real-time Digital Twin Platform, we create a digital copy of the entire grid from production through distribution to end-users, combining geographical, weather, and sensor data with physics-based models and AI. It allows energy providers to optimise their systems in real time, improve operational control, and run simulations of future situations. Our team consists of energy specialists, engineers, data scientists and top-tier consulting alumni and is backed by investors Blue Earth Capital, SEB Greentech Venture Capital, Capricorn Partners, Eneco Ventures, Helen Ventures, and Energiiq. What we’re looking for You’ll join our Digital Twin team, consisting of software engineers, digital twin engineers, and data analysts. We’re at the intersection of software development and engineering, aiming to maximize our sustainable impact through our SaaS platform. You’ll be working on a layer of intelligence (a combination of physics, mathematics, and machine learning) that simulates, analyses, and optimizes heat networks. You’ll be tasked with building generalized software that can be configured by our colleagues in the Customer Solutions & Operations team. You’ll focus on improving our models, control strategies, parameter estimation, and optimization strategies. Our high-level stack Python, GCP, UbiOps, DuckDB, MongoDB, Parquet, Polars. What you'll be doing Develop a deep understanding of the hydraulic and thermodynamic behaviour of heating systems and translate this knowledge into scalable software solutions. Design, build and optimise high-performance Python applications where efficiency, reliability and maintainability are critical. Apply and extend our digital twin technology across innovative, state-of-the-art projects. Drive research and development initiatives, exploring new ideas and transforming them into practical product features. Collaborate closely with software engineers, solution engineers and domain experts to deliver robust, high-quality solutions. Take ownership of your work, planning and managing your tasks independently and, where appropriate, leading the development of a product component. About you Experience developing production-grade Python software, with a solid understanding of software engineering best practices.Hands-on engineer who enjoys solving complex technical problems and thrives at the intersection of software, modelling and applied science.Experience using Git and working within collaborative development environments. A sound understanding of fluid dynamics and thermodynamics. Knowledge of modelling and simulation, control systems, parameter estimation and/or optimisation techniques. A collaborative team player with a strong sense of ownership, accountability and initiative. A BSc or MSc in Applied Physics, Mathematics, Mechanical Engineering, Computer Science, or a related discipline. Nice to have(s) Experience with machine learning and MLOps Familiarity with GIS datasets and tools such as QGIS. Why join? Join an ambitious scale-up that has successfully raised a Series B funding round from an international consortium of investors in the sustainable energy sector. Make a direct impact on sustainability and the energy transition. Be part of an international, inspiring team of talented, creative and collaborative professionals. Enjoy fantastic team events, including off-sites, monthly socials and team gatherings. Thrive in a dynamic, high-performing environment that welcomes new ideas and offers plenty of opportunities to learn and grow. Benefit from a competitive salary and a variable incentive plan (SARs). Receive a competitive benefits package, including an NS Business Card and pension scheme. Checking the boxes but doubting if you should apply? At Gradyent, we support a growth mindset for our teams through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.