Machine Learning Engineer

We are looking for a Machine Learning Engineer (Mid or Junior level) to help us explore and implement novel approaches to help mitigate climate change. You will be applying the latest developments in machine learning to reduce the effects of climate change, and helping turn viable approaches into real-world products.

In the short term, we are focusing on developing projects from solar now casting for electricity system operators, wind forecasting and solar penetration estimation. You will be working with large datasets including weather forecasts, satellite imagery and real‑time electricity generation time‑series. You will work with the entire Open Climate Fix team in delivering a product from data engineering, machine learning, validation and implementation.

You will be part of the team building the solution yourself as well as the opportunity to engage with open‑source contributors.

You will, among other things:

• Be crucial in developing/training new models and evolving our current ML forecast models.
• Run experiments using our models for specific client/projects.
• Keep up to date with the latest ML research and implement them in our ML code base.
• Implement models in live environments and respond to improvements based on real‑world running.
• Work on architecting high‑volume data pipelines and collecting the data with our data team.
• Helping solve various energy sector problems.

• You have a passion for helping the world reduce carbon emissions.
• You have 1-4 years of experience in developing deep learning models in industry or postgraduate academia.
• You have good intuitions about and experience in using 'real‑world data', the ways it can go wrong and how to address them.
• You have strong understanding and experience in using Python and Git, in particular PyTorch.
• You have enthusiasm for learning and ML experimenting.
• You like to work with a cross‑functional team, from research to back‑end and front‑end implementation.

• An undergraduate degree in a relevant subject such as Computer Science, Machine Learning, Data Science, Mathematics, Physics, Engineering, or a related quantitative field.
• A postgraduate degree (Master’s, PhD) in a relevant area would be beneficial, but is not required.
• Equivalent practical experience, research, or industry work is welcomed in place of formal qualifications.

• Experience with modelling using electricity/weather data is an advantage.
• Experience in working with open‑source code and communities is an advantage.
• Experience and interest in writing or talking about your work can be useful.

We know that people from diverse and historically under‑represented backgrounds may be less likely to apply unless they meet every requirement listed. At Open Climate Fix, we care most about your passion for tackling climate change and your potential to succeed in the role. If this position excites you and your values align with our mission, we strongly encourage you to apply, even if you don’t meet every qualification.

You might be exactly who we’re looking for.

Location:

London (Hybrid)

We are a hybrid organisation with a fantastic shared office space in central London. We work in a hybrid setting, with 2 team office days, with the option to use the office more frequently. We also have monthly in‑person days where the whole team attends in person.

The role does not include visa sponsorship (right to work in UK required).

• Salary £40,000 - £60,000 (based on experience)
• Flexible hours around core team working patterns
• 30 days annual leave (plus UK public holidays)
• Private healthcare (post probation period)
• Global travel insurance (post probation period)
• 7% Employer Pension Contribution
• Training & Development budget
• Generous gender‑neutral parental leave
• Working from abroad allowance with up to 4 weeks (timezone UK +/- 3 hours) or 2 weeks from anywhere in the world

At Open Climate Fix, we're on a mission to tackle climate change head‑on by helping slash carbon emissions faster than ever before. We're a passionate team dedicated to building cutting‑edge technology that makes a real difference. Our first focus is on…