Machine Learning Engineer

• 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. You’ll 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 your knowledge and experience with the wider team. You’ll play a key role in fostering 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 our products and services. This includes asking the right questions, identifying high-impact areas, and contributing to the broader data strategy.

This role creates positive change by developing machine learning and GenAI solutions that help energy utilities optimize energy usage, automate operations, and advance the transition to renewable energy, ultimately making sustainable energy more affordable and accessible for all.

• 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 others commonly used in the ML ecosystem.
• Hands-on experience with GenAI APIs and tools, including deployment and integration of GenAI solutions into production systems.
• Experience across the full ML lifecycle, including 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 clearly 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 techniques such as hypothesis testing, significance testing, and probability theory.
• Comfortable working in an agile environment, contributing to iterative development cycles and cross-functional teams.

• 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

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.