Founding Engineer / AI for Energy Transition / Up to £120k + Equity

Founding Engineer (MLOps) - Founding Team | ML Infrastructure | Climate Tech

King's Cross, London (4 days/week)

£90,000–£120,000 + Equity

We're partnering with a well-funded, early-stage climate technology startup that's using cutting-edge machine learning to tackle one of the biggest challenges facing the energy transition, critical mineral mining.

Backed by leading industry investors and already working with enterprise customers, they're now looking for their first ML Ops Engineer to build the infrastructure that will power the next stage of the company's growth.

The Role

This is a true founding infrastructure role.

You'll take ownership of everything that sits between machine learning research and production - building the platforms, pipelines and engineering practices that allow the team to move quickly and scale with confidence.

Working alongside the CTO and ML Engineer, you'll own the ML infrastructure from the ground up, making key architectural decisions from day one.

You'll be responsible for:

• Owning and evolving the company's ML infrastructure and compute environment
• Building and automating scalable data pipelines
• Improving developer workflows and ML engineering practices across the team
• Structuring codebases and deployment workflows to support future growth
• Making key cloud infrastructure decisions (Azure today, AWS is an option)
• Helping bridge the gap between research and production systems

We're looking for someone who...

• Has experience owning ML infrastructure or ML Ops within a startup or scale-up
• Understands how to support researchers while building production-ready systems
• Has worked with large-scale geospatial datasets (this is a key requirement)
• Enjoys making architectural decisions and building systems from scratch
• Wants to join a genuinely early-stage company where they'll have significant ownership
• Thrives in fast-moving environments with lots of autonomy

Tech

• Azure (with the opportunity to evaluate AWS)
• Python
• ML pipelines
• Cloud infrastructure
• CI/CD & automation

The stack is flexible—the focus is on finding someone who can make the right long-term engineering decisions rather than someone tied to a specific cloud provider.

Why join?

• Own the ML infrastructure from day one
• Make foundational technical decisions that will shape the company for years to come
• Equity alongside a competitive salary
• Backed by major industry investors and already working with enterprise customers
• Work directly alongside a highly technical founding team
• Build technology with genuine impact in climate and sustainability

London (King's Cross) | 4 days per week in the office (3 may be considered for the right person)