Founding ML Engineer - Climate Tech

JR United Kingdom; Hounslow; Remote; GBP 50,000 - 80,000; Full time

Job summary

A UK-based climate tech startup seeks a Founding ML Engineer to build scalable systems utilizing cutting-edge AI. The role offers the opportunity for significant ownership and impact, working collaboratively to solve real-world problems while leveraging advanced machine learning tools.

Benefits

High trust environment

Growth-oriented mentorship

Mission-driven work

Qualifications

• Experience building ML-driven applications using LLMs.
• Familiarity with vector databases for scalable performance.
• Startup mindset and ability to navigate ambiguity.

Responsibilities

• Design and implement production-ready retrieval-augmented generation (RAG) pipelines.
• Create scalable ML systems for parsing long-form documents.
• Collaborate with stakeholders to refine use cases.

Skills

Machine Learning

Vector Databases

Deployment

API Integration

Collaboration

Tools

Python

AWS

LangChain

LlamaIndex

Job description

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Founding ML Engineer - Climate Tech, south west london

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Client:

Paradigm Talent

Location:

south west london, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

2

Posted:

06.06.2025

Expiry Date:

21.07.2025

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Job Description:

? London preferred, remote considered (UK-based)

? Early-stage | High ownership | Real-world impact

About the Company

We’re an early-stage technology, our platform makes unstructured documents searchable, explainable, and useful - giving users the insights they need to make faster and more informed decisions.

We’re building a founding team of engineers who are passionate about solving meaningful real-world problems in the climate-tech space using cutting-edge AI. We’re already working with forward-thinking organisations and are now focused on scaling the next version of the product.

The Opportunity

We're looking for a Founding ML Engineer to join our small, mission-driven team. This is a rare chance to build systems from the ground up, define the product alongside users, and work with modern ML tooling - not just in theory, but in production.

What You’ll Do

• Build RAG-Based Systems: Design and implement production-ready retrieval-augmented generation (RAG) pipelines powered by LLMs and vector search.
• Develop ML Infrastructure: Create scalable, modular ML systems for parsing and interpreting long-form unstructured documents.
• Collaborate Closely with Users: Work directly with internal and external stakeholders to refine use cases and deliver high-utility outputs.
• End-to-End Ownership: Operate across the stack—from model experimentation to integration with APIs and UIs.
• Influence Culture & Direction: Help shape technical standards, processes, and company culture as a key early team member.

Who You Are

• Applied ML Engineer: Experience building ML-driven applications using LLMs, with an emphasis on real-world deployment rather than just experimentation.
• Strong with Vector Tech: You’ve worked with vector databases and know how to structure embeddings and retrieval for scalable performance.
• Startup-Minded: You’re comfortable wearing multiple hats and navigating ambiguity with a bias toward action.
• Curious & Fast-Learning: You pick up new tools quickly, iterate fast, and are thoughtful about technical tradeoffs.
• Mission-Aligned: You care about creating tech that solves important problems in a responsible and lasting way.

What We’re Working With

• We’re early-stage and flexible, but current tools include:
• Python (and typical ML ecosystem)
• Open-source and API-based LLMs Retrieval frameworks (e.g., LangChain, LlamaIndex)
• Cloud-native infra (AWS)

We care more about your ability to learn and execute than ticking every tech box.

Why Join

• Shape the Future: Join at the ground floor and influence everything from the product roadmap to team values.
• Mission-Driven Work: Build tools that help organisations make better decisions in complex domains.
• Work Autonomously: High trust, high impact environment with real ownership from day one.
• Growth-Oriented: Work closely with experienced founders and early users to rapidly develop your skills and career.