Overview

We built Neutreeno to transform business at speed and scale by revolutionising decarbonisation. Our software, backed by science from the University of Cambridge, helps companies understand and reduce emissions by mapping resource and emissions flow data to identify the most impactful areas for reduction. Our work with sustainability scientists from the IPCC and IEA informs international climate policy, and our approach has been adopted by leading companies. We recently completed a $5M seed round led by US investors and have been covered by ESGPost, YahooFinance, and BusinessWeekly, with a Cambridge Institute for Sustainability Leadership Earthshot Prize nomination for 2025. We are ready to grow and tap into a $130B addressable market.

About Neutreeno We built Neutreeno to transform business at speed and scale by revolutionising decarbonisation. Our software, backed by cutting-edge Cambridge science, helps companies understand and reduce emissions through data-driven insights. We work with leading sustainability scientists shaping climate policy and are expanding rapidly.

Join us in revolutionising decarbonisation and tapping into the $130B addressable market.

The Role

As a Machine Learning Engineer at Neutreeno, you’ll lead the development of intelligent systems that power our emissions and decarbonisation capabilities. You’ll build platforms that transform complex data into actionable insights for thousands of companies globally, developing AI-driven climate tech that processes vast unstructured data to reveal patterns in global emissions. You’ll collaborate with the climate science team to translate research into production-ready ML solutions, leveraging graph-structured emissions models to understand complex supply chain relationships. You’ll engage with technical stakeholders across industries to build scalable ML systems that drive decarbonisation at global scale.

Key Responsibilities

• Use and fine-tune out-of-the-box models for matching textual and quantitative data to entries in our emissions database with uncertainty estimation
• Develop an emission intensity inference model using deep learning techniques that leverage uncertainty
• Advise on the use of out-of-the-box Large Language Models to extract data from various sources
• Advise on construction of data pipelines to integrate industrial and economic data into our database and generate training data
• Collaborate with climate mitigation scientists and process engineers to translate domain expertise into scalable ML solutions
• Evaluate and recommend ML implementations by balancing upfront setup costs and business value
• Guide integration of out-of-the-box AI tools to enhance internal operations and front-end use cases
• Stay up-to-date with the latest ML theory, techniques, and tools
• Contribute to technical documentation and present ML methodology insights to internal teams and external stakeholders

Required Qualifications

• Master’s or PhD in Computer Science, Machine Learning, Data Science, or a related field
• Strong foundation and practical application of ML techniques, ideally NLPs, LLMs, Bayesian optimisation, and MCMC methods
• Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX, Hugging Face, vLLM)
• Excellent communication skills and ability to explain ML concepts to non-technical stakeholders
• Ability to work effectively in cross-disciplinary teams across engineering, product, and commercial functions

Preferred Qualifications

• Experience with large codebases and collaboration via version control (e.g., Git, GitHub)
• Experience with data scraping and extraction (e.g., Beautiful Soup, LLMs) and cleaning
• Knowledge of uncertainty quantification and probabilistic modelling (e.g., Bayesian optimisation)
• Experience with cloud deployment pipelines (Docker, AWS, CI/CD)
• Familiarity with sustainability or environmental data standards and frameworks

What We Offer

• Opportunity to make a significant impact on global decarbonisation
• Collaborative and innovative environment at the Cambridge Institute for Sustainability Leadership; network with leading startups and climate professionals
• Learning from world-leading mitigation climate scientists
• Hybrid work model (three days a week in our Cambridge office) with flexibility
• Salary £60,000 – 85,000 base DOE
• Stock option plan
• Professional development and growth opportunities
• Company pension
• Private health insurance
• On-site amenities and events
• Work from anywhere for up to two weeks per year

If you’re passionate about using machine learning to make a tangible impact on global decarbonisation, we’d love to hear from you.

Equal Opportunity Neutreeno is an equal opportunity employer committed to creating an inclusive workplace.