Machine Learning Manager

Overview

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. [Employer hidden — sign up to reveal] 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. 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, Schroders Capital and others. Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value. At [Employer hidden — sign up to reveal], 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

We're looking for a Machine Learning Manager to lead the people side of [Employer hidden — sign up to reveal]'s most technically complex team. Rosso is [Employer hidden — sign up to reveal]'s core IP: the AI-powered engine at the heart of how we price, forecast, and optimise energy transactions. The ML engineers who build it work across multiple distinct specialisations simultaneously: time-series forecasting, pricing, optimisation, and classical ML. This role exists because the ML engineers need a dedicated, full-time leader focused entirely on their growth and performance. This is a people leadership role, not a technical authority role. You will work closely with the Rosso Engineering Manager to ensure the ML and software engineering sides of the service collaborate well. [Employer hidden — sign up to reveal] is a Series B company and this is a startup environment.

Responsibilities

• Build a high-performing ML team: Lead hiring, onboarding, performance management, and career development.
• Own the team's operating systems: Build and maintain rituals and structures like sprint cadences, incident review, model monitoring feedback loops.
• Enable technical excellence without owning it: Act as a sounding board for ML engineers.
• Drive collaboration with the Rosso Engineering Manager.
• Represent the team and champion [Employer hidden — sign up to reveal]'s culture.

Requirements

Must haves:

• Proven experience managing ML engineers or scientists (not just software engineers) at varying ranges of experience (Junior to Staff), with enough understanding of the ML lifecycle and core disciplines including forecasting, optimisation, pricing, and classical ML to manage credibly.
• A strong people development track record: 1:1s and performance conversations that actually move people forward, action underperformance, clear progression frameworks, and coaching.
• Experience building and owning team operating systems.
• A strong hiring instinct for ML roles.
• Experience managing a technically diverse team.
• Experience in a startup or high-growth environment.

Bonus points: Background in energy, fintech, or another domain where ML is mission-critical; experience building career frameworks; familiarity with ML and software engineering intersection.

Benefits & Perks

• Competitive salary, reviewed twice a year using real-time market data.
• Stock Options - everyone on the team has ownership.
• 25 days holiday + public holidays + birthday off.
• Remote & flexible working - fully remote across Europe, core hours, no internal meetings on Friday afternoons.
• Home working & wellbeing budgets: Up to £1,200/€1,200 annually for remote setup; up to £150/€150 monthly for wellbeing.

Interview Process

Our processes normally take around 2-3 weeks from first call to offer. First call with Talent Team (30 mins), Behaviour Interview with Head of Data (45 mins), Skills Interview with the Team (75 mins), Culture-Add Interview with Stakeholders (45 mins). We welcome applications from people of all backgrounds.