Founding ML Engineer - Climate Tech

JR United Kingdom; Nottingham; Remote; GBP 60,000 - 90,000; Full time

Job summary

A leading early-stage technology company is seeking a Founding ML Engineer to join their mission-driven team. In this role, you will build systems from the ground up, directly influencing the product and company culture while working with cutting-edge ML tooling in a high-impact environment.

Benefits

High-trust environment

Ownership from day one

Growth-oriented collaboration with experienced founders

Qualifications

• Experience building ML-driven applications using LLMs.
• Strong with vector databases for scalable performance.
• Comfortable in a startup environment, navigating ambiguity.

Responsibilities

• Design and implement production-ready retrieval-augmented generation (RAG) pipelines.
• Create scalable, modular ML systems for parsing long-form unstructured documents.
• Operate across the stack—from model experimentation to API integration.

Skills

Machine Learning

Vector Technology

Python

Cloud Infrastructure

Job description

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Client:

Paradigm Talent

Location:

Nottingham, 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 company whose 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 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 focused on 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 rare chance to build systems from the ground up, define the product alongside users, and work with modern ML tooling—implemented in production, not just in theory.

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: Experience with vector databases and structuring 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 rapidly, and consider technical tradeoffs thoughtfully.
• Mission-Aligned: Committed to creating technology that solves important problems responsibly and sustainably.

What We’re Working With

• Current tools include:
• Python (and typical ML ecosystem)
• Open-source and API-based LLM retrieval frameworks (e.g., LangChain, LlamaIndex)
• Cloud-native infrastructure (AWS)

We value 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 floor.
• Mission-Driven Work: Build tools that help organizations make better decisions in complex domains.
• 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 rapidly.