Boutique executive search specialists for global renewable energy projects.
Collaborate with cross-functional teams to identify challenges and deliver AI-driven solutions.
Develop predictive analytics, forecasting, and optimisation tools to improve operational efficiency.
Manage and structure large datasets, ensuring quality and accessibility for ML applications.
Design, implement, and deploy scalable AI/ML models to support energy and infrastructure operations.
Apply MLOps principles to maintain and continuously enhance deployed ML models.
Build and validate proof-of-concept solutions, ensuring models perform reliably in live environments.
Familiarity with cloud platforms (AWS, Azure, Google Cloud) and microservices architecture.
My client is seeking a Machine Learning Engineer to join their technology team. The role involves developing, implementing, and optimising AI/ML models for real-world energy and infrastructure applications. The ideal candidate will have hands-on experience delivering production-ready ML solutions and a strong understanding of system performance, predictive analytics, and data-driven decision making.
5+ years of experience in ML/AI, preferably in energy, industrial automation, or smart infrastructure.
Strong analytical, problem-solving, and communication skills, with experience working in collaborative teams.
Experience deploying ML models in production using MLOps principles.
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn, and programming in Python, R, MATLAB, or C++.
Location: Birmingham, UK (Hybrid – 3 days in office)