Senior ML Engineer – Document Automation for Global Transactions
| Fully Remote | London-based Scale-up
The Challenge
Imagine transforming a financial regulation process that currently takes days into one that takes just 3 minutes. Our client is revolutionising how complex documentation is processed for transactions worth hundreds of millions of dollars.
What You'll Build
You'll be deploying production ML/NLP/LLM models that actually matter. No research for research's sake – this is about building systems that handle real money, real compliance requirements, and real business impact.
Your technical focus:
Core Requirements:
This isn't your typical ML role. You'll be working in a regulated environment where:
200+ person scale-up with leadership from Microsoft and Google, banking. The 10-person Data & AI team includes Data Scientists, ML Engineers, Data Engineers and analysts who actually ship working products.
Culture: High autonomy, fast-paced, “work hard, play hard” mentality. London office in Paddington with regular team gatherings, but you can work fully remote with optional office days.
What We're NOT Looking For
Simple and fast:
You'll be part of the technical transition from legacy rules-based systems to AI-driven solutions in a sector that desperately needs modernisation. Real business impact, real technical challenges, real money.
| Fully Remote | London-based Scale-up
The Challenge
Imagine transforming a financial regulation process that currently takes days into one that takes just 3 minutes. Our client is revolutionising how complex documentation is processed for transactions worth hundreds of millions of dollars.
What You'll Build
You'll be deploying production ML/NLP/LLM models that actually matter. No research for research's sake – this is about building systems that handle real money, real compliance requirements, and real business impact.
Your technical focus:
- Document parsing, layout analysis, and key information extraction across a wide range of structured and unstructured formats
- Fine-tuning models for document classification, field extraction, and discrepancy detection
- Prompt engineering and LLM chaining to get optimal results from large language models
- Building automated ML pipelines from data prep through to serving
- Integrating ML components into production backend services with robust APIs
Core Requirements:
- 5+ years applied ML experience with NLP, GenAI, and document understanding
- Strong experience with transformer architectures, LLMs/SLMs, and prompt engineering
- Hands-on experience with modern OCR tooling and document layout modelling
- Cloud deployment experience (AWS/GCP/Azure)
- Production Python expertise (they're fully committed to Python)
- Docker development – essential
- API development and model serving experience
- Logistics or supply chain experience
- Information extraction in low-data/noisy conditions
- Anti-fraud or compliance document analysis
- EU time zone location
This isn't your typical ML role. You'll be working in a regulated environment where:
- Human-in-the-loop systems are mandatory for compliance
- Your code needs to be production-ready from day one
- Weekly deliverables are expected (this moves fast)
- You'll work with frameworks like LangChain, Semantic Kernel, and AutoGen
200+ person scale-up with leadership from Microsoft and Google, banking. The 10-person Data & AI team includes Data Scientists, ML Engineers, Data Engineers and analysts who actually ship working products.
Culture: High autonomy, fast-paced, “work hard, play hard” mentality. London office in Paddington with regular team gatherings, but you can work fully remote with optional office days.
What We're NOT Looking For
- PhD researchers focused on theoretical work
- Anyone who needs heavily structured environments
- Traditional ML approaches when modern LLM solutions exist
Simple and fast:
- 30-minute screening with the VP of Data and AI
- 60-minute technical discussion (code samples, no formal tests)
- HR chat
- Decision
You'll be part of the technical transition from legacy rules-based systems to AI-driven solutions in a sector that desperately needs modernisation. Real business impact, real technical challenges, real money.
