Tech Lead Machine Learning Engineer

Overview

Join to apply for the Tech Lead Machine Learning Engineer role at Kaluza

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.

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.

Location
:
London, Bristol, Edinburgh — Hybrid/work model as described above.

Salary
: £80,000 - £100,000

You’ll be part of the centralised Kaluza ML team and wider Data community where you’ll share knowledge, support other MLEs, Analysts and Product teams. You’ll be developing optimisation, ML algorithms and GenAI solutions across Kaluza.

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 Help Desk 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.
• Product ionise 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.

• Proven experience leading teams in real-world ML / AI projects, with a strong understanding of core algorithms, data structures, and model performance evaluation.
• Proficiency in Python, including libraries such as Scikit-learn, Pandas, Num Py, 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.
• Strong analytical and problem-solving skills, with the ability to guide teams through complex challenges while keeping business impact in focus.
• Experience across the full ML lifecycle, including data preprocessing, model training, evaluation, deployment, and monitoring in production environments.
• Expertise with MLOps tools and practices (e.g., MLflow, Sage Maker, Docker, CI/CD pipelines), and the ability to set standards and best practices for the team.
• Excellent communication and presentation skills, capable of clearly articulating technical results and strategic implications to both technical and non-technical stakeholders, including senior leadership.
• Demonstrated track record of stakeholder engagement, leading cross-functional collaboration 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, driving iterative development cycles and mentoring cross-functional teams.
• Some experience with Scala is a plus.

We’re on a mission, we build together, we’re inclusive, we get it done, we communicate with purpose. Our…