Location
Cambridge, UK

Hours
Full Time

Salary
Negotiable, dependent on skills, qualifications and experience

About Neutreeno
Climate change is the defining business challenge of our time, and we're here to solve it. Most decarbonisation solutions count emissions but do nothing to reduce them. We've changed that. We’re Neutreeno, an emissions-to-performance platform, born out of the University of Cambridge's Department of Engineering. We help companies with supply chains and production processes turn emissions data into operational insight, the kind that cuts costs, sharpens decisions, and unlocks genuine competitive advantage. For operations and finance, it's margin they can measure. For sustainability teams, it's progress they can prove. Same data, two audiences, one engine. We’re a fast-moving team that values EQ just as much as IQ. Autonomy, high ownership, speed and no-ego collaboration are at our core. We seek people who care deeply and are eager to work on solving problems bigger than themselves.

About the Role
As a Decarbonisation Model Engineer, you'll sit at the forefront of industrial decarbonisation, identifying, evaluating and modelling the technologies and process changes that cut carbon emissions across complex industries. The role is defined by system-level thinking: treating a client's processes, sites, energy supply and supply chain as one connected system, then finding where a change in energy use, material use or technology delivers the greatest reduction in emissions and cost. Working across sectors like jet engine production, electricity transmission and EV battery manufacturing, you'll sit at the intersection of engineering, sustainability, economics and data science. Your models become part of the product, putting a credible number on every lever: what it costs, what it returns, and what it is worth under today's and tomorrow's carbon prices.

The Work You'll Do
Build bottom-up models from first principles that calculate bespoke decarbonisation levers at scale, accounting for cost, dependencies and implementation time. Quantify energy and material efficiency opportunities, from heat recovery, electrification and utilities to yield losses, material substitution and circular design while identifying Best Available Technologies (BAT) for technology-specific cases. Develop the techno-economic analysis behind each lever: CAPEX and OPEX, cost of abatement, marginal abatement cost curves, and sensitivity analysis that stands up to a client's finance team. Develop our carbon pricing engine across the current pricing landscape (compliance markets, taxation, internal shadow pricing, CBAM) and model client exposure under different price scenarios. Identify where decarbonisation creates value, including green premium pricing for low-carbon products and access to incentives and green finance. Write clear, reproducible Python behind the models and mentor junior engineers.

Benefits
Competitive salary dependent on your skills, qualifications and experience. 25 days annual leave. Year-end performance bonus. Meaningful equity stake to think and benefit like an owner as the company grows. Company pension with NEST. Leading private health insurance with WPA (the only Which? Recommended Provider for Private Medical Insurance). Cycle to work scheme. Hybrid work model fostering teamwork and individual flexibility. Remote working allowance of 2 weeks per year for personal travel, in addition to regular holiday policy. Work from Neutreeno HQ at the Cambridge Institute for Sustainability Leadership, recognised by the FT as one of Europe's leading startup hubs. Great on-site amenities including unlimited free coffee and regular events with global sustainability leaders. A diverse, fast-growing team with 200%+ YoY growth, recent $5M seed round, and recognition as one of Gartner's Coolest Vendor Innovations in Supply Chain Sustainability for 2026. An open-minded, non-hierarchical culture where ideas and ownership matter. The chance to work alongside world-class climate scientists and engineers on one of the most important problems of our time.

Experience
Minimum 3+ years of industry or research experience in techno-economic modelling, with a strong focus on energy and material efficiency and emissions reduction. Proven system-level thinking: able to reason about whole systems and identify where the biggest opportunity sits, rather than optimising components in isolation. Deep working knowledge of energy and material efficiency in industry including heat integration, electrification and fuel switching, and how material flows, yield losses and substitution drive embodied emissions. Strong command of carbon accounting and life cycle assessment, including Scope 1, 2 and 3 inventories, product carbon footprints and relevant frameworks (GHG Protocol, ISO 14064 / 14067, SBTi, CBAM). Costing proficiency across techno-economic analysis (CAPEX/OPEX, abatement cost, MACCs), project finance (NPV, IRR, payback, discount rates) and carbon pricing (ETS, carbon taxes, internal shadow prices). Expert Python skills for quantitative modelling (pandas, NumPy), with discipline to make models reproducible, validated and version-controlled (Git/GitHub). Familiarity with using LLMs and agentic-AI workflows to build and enhance decarbonisation roadmaps. Outstanding communication skills, able to convey technical concepts to both technical and non-technical audiences.

About You
You are passionate about addressing climate change through innovative engineering solutions. You thrive in a fast-moving, collaborative environment valuing both emotional and intellectual intelligence. You take ownership of your work and enjoy mentoring others. You are eager to work on complex, system-level challenges that have real-world impact.

Qualifications
Masters or PhD in Industrial, Chemical, Process or Mechanical Engineering.

Preferred Qualifications
Experience with process simulation software (e.g. Aspen Plus, HYSYS). Experience building marginal abatement cost curves or decarbonisation roadmaps for large industrial clients. Knowledge of optimisation or machine learning applied to process optimisation and emissions reduction.