Machine Learning Engineer – Solar & Energy

Vecta Ltd; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Vecta Ltd in Europe is on a mission to accelerate the energy transition. As an ML Engineer, you will build, train, and deploy models that predict solar generation, optimise energy storage, forecast demand, and help keep the grid balanced.

You will work with weather data, sensors, and market prices across Europe, design ML pipelines, and collaborate with engineers to deploy models into real-time energy management systems. We value shipping reliable solutions and a passion for climate impact.

Qualifications

• 2+ years of production ML experience.
• Strong Python skills with ML frameworks.
• Experience with time series forecasting.
• Experience with cloud platforms and MLOps.
• Interest in energy, climate, or sustainability.

Responsibilities

• Build and deploy ML models for solar forecasting and energy optimisation.
• Work with time series data from weather systems, sensors, and smart meters across Europe.
• Design and maintain ML pipelines—from data ingestion to training to production inference.
• Collaborate with engineers to integrate models into real-time energy management systems.
• Continuously improve model performance through experimentation and validation.
• Help shape the ML roadmap and identify new opportunities to apply AI across the business.

Skills

Python

ML frameworks

Time series forecasting

Cloud & MLOps

Energy/climate interest

Tools

TensorFlow

PyTorch

scikit-learn

AWS

GCP

Azure

Job description

This solar company is on a mission to accelerate the energy transition across Europe. They're building the infrastructure and intelligence layer that makes renewable energy work at scale — and ML is at the heart of it. If you want your work to matter, this is the place. As an ML Engineer, you'll build, train, and deploy models that solve real problems: predicting solar generation, optimising energy storage, forecasting demand, and keeping the grid balanced. The data is rich — weather, sensors, market prices, consumption patterns — and the problems are genuinely hard. This isn't big tech ML for ads or engagement metrics. It's applied machine learning for the climate crisis. You'll work with a team that cares deeply about impact, ships fast, and believes that software can change the world. If that sounds like you, keep reading.

Responsibilities

• Build and deploy ML models for solar forecasting, demand prediction, and energy optimisation
• Work with time series data from weather systems, sensors, and smart meters across Europe
• Design and maintain ML pipelines — from data ingestion to training to production inference
• Collaborate with engineers to integrate models into real-time energy management systems
• Continuously improve model performance — experimenting, validating, and iterating
• Help shape the ML roadmap and identify new opportunities to apply AI across the business

Qualifications

• An ML Engineer with 2+ years of experience building and deploying models in production.
• Strong Python skills and hands-on experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Comfortable with time series data and forecasting problems.
• Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices.
• Curious about energy, climate, or sustainability — or excited to learn.
• A pragmatic builder who cares about shipping things that work, not just impressive prototypes