Machine Learning Engineer

Kaluza Ltd.
Charing Cross, United Kingdom
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
£ 87K

Job location

Charing Cross, United Kingdom

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Data Structures
Statistical Hypothesis Testing
Iterative and Incremental Development
Python
Machine Learning
NumPy
Software Deployment
Delivery Pipeline
Data Strategy
GIT
Pandas
Scikit Learn
Performance Monitor
Kafka
Machine Learning Operations
Software Version Control
Docker
Databricks
Microservices

Job description

  • 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.

Requirements

Do you have experience in Software deployment?, * 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.
  • 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, 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.
  • Some experience with Scala is a plus

We want the best people

We're keen to meet people from all walks of life - our view is that the more inclusive we are, the better our work will be. We want to build teams which represent a variety of experiences, perspectives and skills, and we recognise talent on the basis of merit and potential.

Benefits & conditions

Our values are not words on a wall - they are at the heart of our culture. They are how we make decisions and how we treat each other. They are concrete and clear, and reflect what we as people, and as a business, really care about.

Kaluza's vision is to power a world where net-zero is within everyone's reach. Would you be interested in joining us to help achieve this?

From us you'll get

  • 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…

Even better? You'll have access to these benefits from day 1 when you join.

About the company

Kaluza is the Energy Intelligence Platform, turning energy complexity into seamless coordination. We help energy companies overcome today's challenges while accelerating the shift to a clean, electrified future. Our platform orchestrates millions of real-time decisions across homes, devices, markets and grids. By combining predictive algorithms with human-centred design, Kaluza makes clean energy dependable, affordable and adaptive to everyday life. With teams across Europe, North America, Asia and Australia, and a joint venture with Mitsubishi Corporation in Japan, we power leading companies including OVO, AGL and ENGIE, as well as innovators like Volvo and Volkswagen. At Kaluza we embrace a flexible, hybrid work model that balances autonomy with the power of in-person connection. Many of our teams find value in coming together regularly to collaborate, strengthen relationships, and accelerate progress. We're focused on shaping thoughtful, team-driven approaches that support both business impact and individual well-being. Where in the world of Kaluza will I be working? 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. What will I be doing? 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.

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