Boutique executive search specialists for global renewable energy projects.
Build and validate proof-of-concept solutions, ensuring models perform reliably in live environments.
Manage and structure large datasets, ensuring quality and accessibility for ML applications.
Collaborate with cross-functional teams to identify challenges and deliver AI-driven solutions.
Develop predictive analytics, forecasting, and optimisation tools to improve operational efficiency.
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.
Familiarity with cloud platforms (AWS, Azure, Google Cloud) and microservices architecture.
5+ years of experience in ML/AI, preferably in energy, industrial automation, or smart infrastructure.
Experience deploying ML models in production using MLOps principles.
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.
Strong analytical, problem-solving, and communication skills, with experience working in collaborative teams.
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)