Staff Machine Learning Engineer

📈 Who We Are:

We have built the new way for energy to be transacted.

tem exists to fix a creaking energy market. Today's wholesale system is stacked in favour of the few - a relic of the oil and gas era, riddled with markups and middlemen. We're changing that.

Our product, RED™, is built on a proprietary pricing engine that bypasses the wholesale market, enabling businesses to buy energy produced by renewable generators directly. That means clear, auditable transactions that ensure affordable bills and fair compensation - giving every business real ownership and control over where their energy comes from.

Since launching in 2021, we've saved UK businesses and generators over £25 million, powering a growing network of forward-thinking companies, from Pizza Pilgrims to Silverstone.

Backed by top-tier VCs including Atomico and Albion, we're creating a new category in energy - one that's decentralised, direct, and built on trust.

🏅 The Role:

Do you want to work on some of the most complex and commercially meaningful problems in energy?

Energy markets today are opaque, inefficient, and expensive. At tem, we’re building the intelligence layer that reduces the cost of transacting electricity and unlocks access to renewables — by developing advanced modelling, pricing, and decision systems that power how energy is bought and sold.

We’re looking for a Staff Machine Learning Engineer to play a key hands-on role in designing, building, and scaling the models and data systems that sit at the heart of our platform. This role combines applied machine learning, optimisation, and production engineering — with real commercial impact.

You’ll work on high-impact, greenfield problems where there is limited precedent, helping bring core modelling capability fully in-house and into production. This is an opportunity to shape not only our systems, but how intelligence is applied across energy markets at scale.

🚀 Responsibilities

• Build core modelling systems: Design, implement, and operate machine learning and quantitative models that power pricing, matching, forecasting, and decision-making across our platform — from research through to production.

• Solve complex applied problems: Translate ambiguous business challenges into robust modelling approaches, balancing accuracy, scalability, interpretability, and commercial outcomes.

• Ship production-grade ML: Develop and maintain end-to-end ML systems in the cloud (AWS preferred), including data pipelines, training workflows, evaluation frameworks, monitoring, and retraining processes.

• Develop proprietary capability: Design high-quality internal modelling systems that reduce reliance on third-party logic and evolve as our product and market understanding grows.

• Collaborate cross-functionally: Work closely with product, engineering, and commercial teams to turn business needs into effective technical solutions. Communicate clearly with both technical and non-technical stakeholders.

• Raise technical standards: Contribute to best practices in experimentation, modelling discipline, reproducibility, and code quality. Provide mentorship and technical guidance to engineers and data scientists.

🎯 Requirements

Must-haves

• Strong quantitative background: Experience applying machine learning, optimisation, or statistical modelling in real-world systems.

• Hands-on ML experience: Proven ability to build, evaluate, and ship models that drive meaningful business outcomes.

• Production mindset: Experience designing, deploying, and maintaining cloud-based ML systems.

• First-principles problem solving: Comfortable operating in ambiguous, greenfield environments where structure must be created.

• Strong Python skills: Experience with the modern data science and ML ecosystem.

• Commercial awareness: Understands how modelling decisions affect risk, cost, and user outcomes.

Nice-to-haves

• Advanced degree (or equivalent experience) in applied maths, machine learning, statistics, or related fields

• Experience with pricing, allocation, forecasting, or decision systems

• Familiarity with regulated or infrastructure-heavy domains (e.g. energy, fintech, logistics)

• Experience with time series modelling, probabilistic methods, or experimentation frameworks

• Exposure to MLOps practices and AWS-based data platforms

✨ Benefits & Perks:

• Competitive salary - our current band for this role is £105,000 or equivalent in local currency.

  • We review salaries twice a year using real-time market data, with transparent, consistent pay for the same role and level.

• Stock Options - everyone on the team has ownership in our mission.

• 25 days holiday + public holidays - Swap public holidays for ones that matter most to you. Plus, get an extra day off for your birthday 🎉.

• Remote & flexible working - We’re fully remote with clear core hours, and no internal meetings on Friday afternoons.

• Home working & wellbeing budgets:

  • Up to £1,200 / €1,200 annually to upgrade your remote setup (co-working passes, equipment, etc.).

  • Up to £150 / €150 monthly on anything that supports your wellbeing - from therapy to gym memberships to meditation apps.

🗣️ Interview Process:

Our processes normally take around 3-4 weeks from first call to offer - please let us know about any adjustments to timelines that may be required.

1. First call with our Talent Team (30 min). This is to understand your experience, motivations, and discuss the role in more detail.

2. Behaviour Interview with our Head of Data (45 min). This is your chance to really understand the role, the expectations, and ensure alignment on ways of working.

3. Technical Interviews with the Team (90 mins). You’ll meet members of the team, and one of our Co-Founders, to dig into your technical skills around modelling and machine learning engineering.

4. Culture-Add Interview with Stakeholders (45 min). The final session will be with our CEO and CTO, and will explore how your values align with ours, and is designed to be a genuine two-way conversation, your chance to understand what it’s really like to work at tem.

We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you’re excited about this role but not sure you meet every requirement, we’d still love to hear from you. Your unique perspective could be exactly what we’re looking for.