Machine Learning Engineer

Job title: Machine Learning Engineer

Location: London, Bristol, Edinburgh

Salary: £63,000 - £81,000

Kaluza reimagines energy to bring net-zero within everyone’s reach. The Kaluza Platform enables energy utilities to unlock the full value of a radically changing energy system and propel us to a future where renewable energy is sustainable, affordable and accessible for all. From automating and simplifying core operations including billing to create a lower-cost, higher-engagement experience, to optimising energy usage across smart devices in the home, we turn tough challenges into win-win-win outcomes for customers, suppliers and the energy system.

At Kaluza we embrace a flexible, hybrid work model that balances autonomy with the power of in-person connection. We’re focused on shaping thoughtful, team-driven approaches that support both business impact and individual well-being. We also prioritise meaningful company-wide gatherings like our annual conference and end-of-year celebrations, that bring us together to align, connect, and celebrate.

Data is the foundation of everything we do, and to deliver our vision we need curious, tenacious people who can turn this data into strategy and actions with their expertise. As an MLE at Kaluza, you’ll help product teams identify patterns and solve challenges with data. Projects include forecasting, recommenders and helpdesk ticket classification.

• Develop ML and GenAI Solutions: Design and implement machine learning using Python, leveraging data technologies such as Databricks, Kafka, and the AWS cloud environment. Our architecture is based on microservices, allowing for dynamic deployment of new features.
• Productionise Algorithms: Deploy algorithms into production environments where they can be tested with customers and continuously improved. Automate workflows, monitor performance, and maintain data science products using best practices for tooling, alerting, and version control (e.g., Git).
• Contribute to a Collaborative Data Science Culture: Share knowledge with the wider team and foster an ML/AI community that values openness, collaboration, and innovation.
• Identify Opportunities for Impact: Help uncover new opportunities where ML/AI can add value across products and services, including contributing to the broader data strategy.

• Proven experience in a real-world ML/AI role with strong understanding of core algorithms, data structures, and model performance evaluation.
• Proficiency in Python, including libraries such as Scikit-learn, Pandas, NumPy, and related ML tooling.
• Hands-on experience with GenAI APIs and tools, including deployment and integration of GenAI solutions into production systems.
• Strong analytical and problem-solving skills with the ability to approach complex problems methodically while keeping business impact in mind.
• Experience across the full ML lifecycle: data preprocessing, model training, evaluation, deployment, and monitoring in production environments.
• Experience with MLOps tools and practices (e.g., MLflow, SageMaker, Docker, CI/CD pipelines).
• Excellent communication and presentation skills, capable of articulating technical results to both technical and non-technical stakeholders, including senior leadership.
• Track record of stakeholder engagement, collaborating cross-functionally with product, engineering, and business teams.
• Solid foundation in statistics, including hypothesis testing, significance testing, and probability theory.
• Comfortable working in an agile environment, contributing to iterative development cycles and cross-functional teams.
• Some experience with Scala is a plus.

• Pension Scheme
• Discretionary Bonus Scheme
• Private Medical Insurance + Virtual GP
• Life Assurance
• Access to Furthr - a Climate Action app
• Free Mortgage Advice and Eye Tests
• Perks at Work - access to thousands of retail discounts
• 5% Flex Fund to spend on the benefits you want most
• 26 days holiday
• Flexible bank holidays, giving you an additional 8 days which you can choose to take whenever you like
• Progressive leave policies with no qualifying service periods, including 26 weeks full pay if you have a new addition to your family
• Dedicated personal learning and home office budgets
• Flexible working — we trust you to work in a way that suits your lifestyle
• And more…

From us you’ll get these benefits from day 1 when you join. Find out more about working in Kaluza on our careers page and LinkedIn.