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Machine Learning Engineer

Usepassionfruitvia Jack & Jill· London, England, United Kingdom· £100,000–£140,000/yrEquitySponsorship
Posted 7 Aug 2026 · Added 7 Aug 2026, 20:57
UsepassionfruitSoftware developmentfounded 2021
AI summary

You will develop and deploy production-grade LLM-powered agentic systems with persistent memory, tool orchestration, and RAG pipelines, integrating with Google Ads, Meta, and CRMs. You will build autonomous agents for marketing operations at a Series A startup building an AI-native teammate for marketing teams. As the second ML hire, you will shape the production stack and product roadmap.

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Job Title

Machine Learning Engineer

Salary

£100k-£140k + Equity

Company Description

Usepassionfruit.com is a $14M Series A startup backed by Seaya, firstminute, and Playfair, building an AI-native teammate for marketing teams. We are automating complex marketing operations—from campaign briefs to paid media analysis—for mid-market brands with high-performance, autonomous agentic systems.

Job Description

As the second ML hire, you will design and deploy production-grade agentic systems that automate complex marketing operations. You'll build persistent agents with memory and tool use, integrating deeply with ad platforms and CRMs to handle everything from performance reporting to creative review for high-growth brands like the Atlanta Braves and ADT.

Location

London, UK

Why this role is remarkable

Join a rocket ship that scaled from $0 to $2M ARR in just four months, with usage growing 6x recently and the company nearing profitability.

Work at the cutting edge of production AI, moving beyond prototypes to deploy agentic systems that handle real-world marketing workflows for enterprise clients.

Enjoy meaningful ownership as a founding member of the ML team, directly shaping the production stack and product roadmap in a fast-paced environment.

What You Will Do

Develop and deploy LLM-powered agentic systems featuring persistent memory, tool orchestration, and multi-step marketing workflow automation.

Integrate models with live data sources including Google Ads, Meta, and CRMs to create autonomous performance and compliance agents.

Iterate on RAG pipelines, retrieval strategies, and domain-specific fine-tuning to improve the accuracy and reliability of marketing-specific AI workflows.

The ideal candidate

Proven experience building and shipping production ML/LLM systems, specifically involving RAG, agentic frameworks, or complex workflow orchestration.

Expert proficiency in Python with solid software engineering fundamentals, including experience building robust APIs and data pipelines.

Thrives in a fast-moving product environment and possesses the technical curiosity to experiment with new technologies like Elixir or specialized marketing analytics.