About Neutreeno

We built Neutreeno to transform business at speed and scale by revolutionising decarbonisation. Our innovative software, backed by cutting-edge science from the University of Cambridge, transforms how companies understand and reduce their emissions. By leveraging decades of research in resource and emissions flow data mapping, we identify the most impactful areas for emissions reduction, enabling companies to make strategic, data-driven decisions.

Working alongside leading sustainability scientists from the IPCC and IEA who shape international climate policy, we're creating a new paradigm in decarbonisation technology. Our approach has already been adopted by the world's largest companies. With our recent $5M seed round led by US investors, and coverage in ESGPost, YahooFinance, BusinessWeekly, and a nomination by Cambridge Institute for Sustainability Leadership for the 2025 Earthshot Prize, we're ready to grow.

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. Working at the cutting edge of machine learning and sustainability, you'll build platforms that transform complex data into actionable insights for thousands of companies globally. Your innovations will directly power breakthrough solutions that identify critical decarbonisation opportunities across entire industries and supply chains. You'll push the boundaries of what's possible with AI-driven climate tech developing advanced models that process vast amounts of unstructured data to reveal hidden patterns in global emissions. You'll collaborate with our climate science team to translate cutting-edge research into production-ready ML solutions, leveraging our graph-structured emissions models to understand complex supply chain relationships. You'll engage with technical stakeholders across industries, building 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 our emission intensity inference model using deep learning techniques that leverage uncertainty
• Advise on the out-of-the-box Large Language Models to extract data from a variety of sources
• Advise on construction of data-pipelines to integrate industrial and economic data into our database and to generate training data for our models
• Collaborate with climate mitigation scientists and process engineers to translate domain expertise into scalable ML solutions
• Evaluate and recommend appropriate ML implementations by balancing upfront setup costs and effort against business value and company goals
• Guide the integration of out-of-the-box AI tools to enhance internal operations and support front-end use cases
• Stay up-to-date with the latest ML theory, techniques, and out-of-the-box tools
• Contribute to technical documentation and present ML methodology insights to both internal teams and external stakeholders

Required Qualifications

• Master's or PhD in Computer Science, Machine Learning, Data Science, or related field
• Good foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs
• Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering)