Senior Staff Machine Learning Engineer - Pricing

📈 Who We Are: We are rebuilding the energy transaction, making it transparent and fair. Our goal is to put power back where it belongs, in the hands of customers and to take on one of the most critical problems of our century, access to low cost electricity. tem exists to fix a broken global energy market that’s long favoured legacy operators, intermediaries, and opaque pricing. Today’s electricity system was not designed for rapid decarbonisation, AI-driven efficiency or fair access for the actual users - businesses and generators. We’ve built the first AI native transaction infrastructure to reinvent how electricity is bought, sold and priced. Our technology is designed to cut out the inefficient fees, automate complex market flows, and bring transparency and fairness to energy transactions at scale. In late 2025, after extraordinary growth, we closed a $75 million Series B - led by Lightspeed Venture Partners with participation from Albion, Atomico, Allianz, Hitachi Ventures, Hitachi Ventures, Schroders Capital and others - positioning us for global expansion, deeper product innovation and category leadership. We’re scaling internationally and building toward a future where AI-driven infrastructure is foundational to electricity markets worldwide. Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value, proving that modern software and AI can transform an industry built on legacy systems. At tem, we’re not just building another energy company, we’re rearchitecting market infrastructure so that transparency, efficiency and sustainability become the default, not the exception. 🏅 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 it’s exposure across its portfolio. This is a hands-on, senior individual contributor role with significant technical leadership and organisation-wide influence. You will work closely with other MLEs, software engineers and MLOps to bring models to production, and carry real ownership of the technical direction and accountable for its performance. 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 systems that worked and have learned from the times it hasn'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 con…