Senior Machine Learning Engineer

Senior Machine Learning Engineer

Location: Remote (Bristol)

Company

Description:

Energy technology company building AI-driven energy intelligence systems

Join a company developing an Energy Intelligence Platform that applies machine learning and Generative AI to optimise decision‑making across energy systems and markets. You’ll design and deploy production‑grade ML solutions, working across real‑time and batch data environments to deliver measurable business impact. This is a hands‑on ML engineering role focused on taking models from prototype to scalable production.

You’ll join a centralised ML team in a collaborative, product‑led environment where experimentation and automation are core to the culture. The role offers ownership over ML system design, production deployment, and MLOps standards within a hybrid UK setup. You’ll work on high‑impact systems used by major enterprise partners, influencing real‑world energy operations.

• Design and implement ML and GenAI solutions using Python and Databricks, focusing on forecasting and recommendation systems.
• Product ionise algorithms within a microservices architecture on AWS, automating deployment, monitoring, and iteration of models based on customer feedback.
• Build and maintain data and model pipelines using Kafka for real‑time data and Databricks for batch processing and feature engineering, ensuring robust data quality.
• Define and implement MLOps best practices including model versioning, CI/CD for models, and experiment tracking using MLflow and Docker.
• Take ownership of monitoring and performance evaluation for production models, driving continuous improvement strategies.
• Collaborate closely with Product, Engineering, and Business stakeholders to identify opportunities, translate requirements into workable ML solutions, and discuss technical trade‑offs and ROI with senior leadership.

• You have extensive experience as a Machine Learning Engineer, with a strong focus on practical application in production environments.
• You’re proficient in Python and familiar with tools like Databricks, Kafka, AWS, and Docker.
• You understand the intricacies of MLOps and have experience with best practices in model versioning and CI/CD.
• You possess solid experience in building and deploying machine learning models that deliver measurable value.
• You’re a team player who thrives in collaborative settings and enjoys mentoring fellow engineers and data scientists.
• You have excellent communication skills, allowing you to translate complex concepts into understandable insights for technical and non‑technical stakeholders.

Python
• Databricks
• Kafka
• AWS
• Docker
• MLflow
• Scala

This is a real, live role that Vecta is currently recruiting for on behalf of a partner company.