Founding ML Engineer - Climate Tech

JR United Kingdom; Swindon; Remote; GBP 55,000 - 85,000; Full time

Job summary

A startup in the climate-tech space seeks a Founding ML Engineer to join its mission-driven team. This role involves building systems that utilize cutting-edge AI to make unstructured documents usable, influencing product and company culture while working autonomously in a high-impact environment.

Benefits

High-trust environment

Influence product roadmap

Collaborate with experienced founders

Growth opportunities

Qualifications

• Experience building ML-driven applications with LLMs.
• Strong with vector tech, capable of using vector databases.
• Startup-minded and comfortable navigating ambiguity.

Responsibilities

• Design and implement production-ready RAG pipelines using LLMs.
• Create scalable ML systems for parsing unstructured documents.
• Manage model experimentation to API and UI integration.

Skills

Machine Learning

Vector Databases

API Integration

Python

Tools

AWS

LangChain

LlamaIndex

Job description

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Client:

Paradigm Talent

Location:

Swindon, Wiltshire, 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:

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London preferred, remote considered (UK-based)

Early-stage | High ownership | Real-world impact

About the Company

We’re an early-stage technology company whose platform makes unstructured documents searchable, explainable, and useful—providing users with insights for faster, more informed decisions.

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

The Opportunity

We’re looking for a Founding ML Engineer to join our small, mission-driven team. This is a unique opportunity to build systems from scratch, define the product with users, and work with modern ML tools—practical, not just theoretical.

What You’ll Do

• Build RAG-Based Systems: Design and implement production-ready retrieval-augmented generation (RAG) pipelines using 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 stakeholders to refine use cases and deliver high-utility outputs.
• End-to-End Ownership: Manage everything from model experimentation to API and UI integration.
• 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 with LLMs, focusing on real-world deployment.
• Strong with Vector Tech: Experience with vector databases, embeddings, and retrieval for scalable performance.
• Startup-Minded: Comfortable wearing multiple hats and navigating ambiguity with a bias toward action.
• Curious & Fast-Learning: Quick to learn new tools, iterate fast, and thoughtful about tradeoffs.
• Mission-Aligned: Committed to creating responsible tech that solves important problems.

What We’re Working With

• Tools include Python (and typical ML ecosystem), open-source and API-based LLM retrieval frameworks (e.g., LangChain, LlamaIndex), and cloud infrastructure (AWS).

We prioritize your ability to learn and execute over ticking every tech box.

Why Join

• Shape the Future: Influence product roadmap and team values from the ground up.
• Mission-Driven Work: Build tools that help organizations make better decisions.
• Work Autonomously: High-trust, high-impact environment with ownership from day one.
• Growth-Oriented: Collaborate with experienced founders and early users to develop your skills and career.