Senior Staff Machine Learning Engineer - Pricing

Job description

📈 Who We Are: We are rebuilding the energy transaction, making it transparent and fair. We're rebuilding how energy is bought and sold. That means cutting out middlemen, connecting businesses directly with renewable generators, and ensuring every transaction is traceable and transparent. We're a 160+ person team - operators, data scientists, engineers, customer champions and energy experts - backed by top-tier investors including Lightspeed Venture Partners, Hitachi Ventures, Allianz, AlbionVC and Atomico. We closed a $75M Series B round in early 2026, taking our total funding to $94M, and we now power energy for over 4,000 UK businesses across 8,500+ sites, with over £75m in value returned to businesses and generators so far. We're a technology company solving the energy industry, not an energy company. Some people call us a neo-utility, the neo-bank idea, applied to energy. The industry is noticing. We were crowned Europe's Most Exciting Tech Company at the GP Bullhound Allstars awards https://www.gpbullhound.com/articles/allstars-awards-2026-winners-announced/, came in at #6 on LinkedIn's Top Startups 2026 https://www.linkedin.com/pulse/linkedin-top-startups-2026-20-uk-companies-rise-linkedin-news-uk-xoffc in the UK, #7 on the Scaling Europe 50 https://scalingeurope.co.uk/ of Europe's fastest-growing companies, and #14 on Sifted's AI 100 https://lnkd.in/p/ehxWgJyc. Learn more about us on our website https://www.tem.energy/. 🏅 The Role: Rosso is tem's core IP, the transaction infrastructure that prices electricity for thousands of businesses, balances portfolios in real time, and sits on the critical path for every deal tem closes. Machine learning is at the heart of Rosso, combining forecasting, optimisation and classical ML to process billions of data points and drive thousands of automated decisions a day. Every inference shapes the prices our customers see, so you can immediately see the impact of your work. We have proved the concept with MVPs and POCs to grow to 2% of the UK market. Now we want to take it to the next level and build towards a state of the art solution, to fuel our expansion in the UK and take Rosso international. We're looking for a Senior Staff Machine Learning Engineer to lead pricing ML within Rosso, building a platform that proactively drives growth by targeting the right customers to sign at the right time. Your primary focus will be the pricing engine, which sets the fees added to every quote tem serves, carefully balancing growth and margin. You will also contribute to the systems which manage both short and long-term imbalance decisions to determine how tem deals with its exposure across its portfolio. This is a hands-on, senior individual contributor role. You own the technical direction of pricing by building it: most of your week is writing and shipping production code. It is not a people leadership role, and not an architecture role where others do the implementing. The right person is energised by the greenfield environment: comfortable taking on ambiguity and able to make progress before the path is fully defined. They have built pricing, trading or optimisation systems that worked, ideally in energy or another market-driven domain, and have learned from the times they haven't. They'll bring that hard-won judgment to a system where the foundations are still being laid, and where early decisions compound. Success will be turning our current reactive system into a pricing engine which proactively drives growth by targeting the right customers to sign at the right time. 🚀 Responsibilities: - Own the technical direction for pricing ML: Define what to build and how within the pricing engine, setting the strategy and roadmap for pricing machine learning as a core piece of tem's IP. - Build ML systems for price optimisation: Design and implement models that dynamically set prices, balancing the trade-off between signing probability, portfolio balance and margin maximisation. - Solve imbalance problems: Develop probabilistic models to optimise risk management and short-term balancing decisions in a highly dynamic environment. - Bridge modelling and production: Own the modelling and data layer while working closely with software engineers and MLOps to ensure models are architected for production, contributing to system design decisions that affect performance and reliability. - Communicate pricing decisions clearly: Articulate model behaviour, assumptions, and trade-offs to other technical stakeholders so that pricing decisions are understood across the teams that depend on them. 🎯 Requirements: Must-haves: - Deep experience building ML systems for pricing, revenue optimisation, or decision-making under uncertainty, with a track record of models that went from concept to production and delivered measurable commercial impact. - A quantitative background in a domain where prices, forecasts and risk interact: energy markets, power trading, batteries