At a Glance
- Tasks: Lead the development of innovative ML and GenAI solutions to transform energy systems.
- Company: Join Kaluza, a forward-thinking tech company focused on sustainable energy.
- Benefits: Enjoy competitive salary, flexible working, and generous holiday policies.
- Why this job: Make a real impact in the renewable energy sector while advancing your career.
- Qualifications: Experience in ML projects, strong Python skills, and a collaborative mindset.
- Other info: Be part of a dynamic team with excellent growth opportunities and a supportive culture.
The predicted salary is between 68000 - 82000 £ per year.
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
Where you will 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 you will be doing:
- 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.
Qualifications:
- 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, 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 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, SageMaker, 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.
Why this role: We’re on a mission, we build together, we’re inclusive, we get it done, we communicate with purpose. Our values are at the heart of our culture and reflect what we care about as people and as a business.
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…
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. If you’re excited about joining us and think you have some of what we’re looking for, we’d love to hear from you.
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Technology, Information and Internet
Machine Learning Engineer - Tech Lead in Bristol employer: Kaluza
Contact Detail:
Kaluza Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Tech Lead in Bristol
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with Kaluza employees on LinkedIn. A friendly chat can sometimes lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it’s GitHub repos or a personal website, let your work speak for itself. This is your chance to shine!
✨Tip Number 3
Prepare for interviews by practising common ML scenarios and problem-solving questions. Get comfortable explaining your thought process and how you tackle challenges. Remember, they want to see how you think!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Kaluza team. Let’s get you that dream job!
We think you need these skills to ace Machine Learning Engineer - Tech Lead in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Python, ML algorithms, and any relevant projects you've led. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for ML and how you can contribute to Kaluza's mission. Be sure to mention specific projects or experiences that demonstrate your expertise and fit for the role.
Showcase Your Collaborative Spirit: At Kaluza, we value teamwork and collaboration. In your application, highlight instances where you've worked with cross-functional teams or mentored others. This will show us that you're a great fit for our culture!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team!
How to prepare for a job interview at Kaluza
✨Know Your Algorithms
Brush up on your understanding of core machine learning algorithms and their applications. Be ready to discuss how you've implemented these in real-world projects, especially in Python using libraries like Scikit-learn and Pandas.
✨Showcase Your Leadership Skills
As a Tech Lead, you'll need to demonstrate your ability to guide teams through complex challenges. Prepare examples of how you've led cross-functional collaborations and engaged stakeholders effectively in previous roles.
✨Familiarise Yourself with MLOps
Get comfortable discussing MLOps tools and practices, such as MLflow and Docker. Be prepared to explain how you've used these tools to automate workflows and maintain data science products in production environments.
✨Communicate Clearly
Practice articulating technical results and strategic implications to both technical and non-technical audiences. Think of examples where you've successfully communicated complex ideas, as this will be crucial in your role at Kaluza.