Do you want to build production-grade ML systems powering the clean energy transition?
Have you deployed and scaled ML models on AWS in real-world environments?
Are you ready to take ownership of MLOps in a fast-growing cleantech scale-up?
A rapidly scaling London-based energy tech company is building an intelligent EV charging and energy optimisation platform used across multiple countries. They've combined proprietary tech, deep data capability and strong industry partnerships to accelerate the shift to sustainable transport. The Data team is now expanding to support growing ML workloads.
They're hiring an MLOps Engineer to own and scale ML infrastructure across computer vision and broader DS/ML use cases. This role is critical to ensuring models are robust, reproducible and production-ready.
Key responsibilities:
• Deploy, manage and monitor ML models in production
• Own MLflow, experimentation tracking and reproducibility
• Build scalable training and deployment pipelines
• Implement CI/CD for ML workflows
• Optimise AWS infrastructure for performance and cost
• Ensure reliability and monitoring of ML endpoints
Key details:
• Salary: £80,000–£110,000 + discretionary bonus
• Working: Hybrid, 3 days per week in London
• Stack: Python, MLflow, AWS (SageMaker), CDK, Docker
• Visa: Cannot sponsor
Interested? Please apply below.