Backend Software Engineer – Applied ML, LLM Systems

🕒 July 16

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Dwelly

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

💼 Consulting

📦 Logistics

🏨 Hospitality

💰 Seed on 2024-05

Consulting • Logistics • Hospitality

Dwelly is an acquisitions and succession-planning platform focused on independent UK lettings agencies. It offers free valuations, competitive cash-out offers, and tailored exit deals while preserving agency branding and client relationships. Dwelly runs a transparent, collaborative due diligence process and uses technology and AI to modernize operations post-acquisition, enabling owners to exit smoothly and profitably.

📋 Description

• Build systems that extract structured data from emails, documents and other unstructured sources. • Enrich migrated client, landlord, tenant and property records with useful information from communication history. • Develop solutions that summarise a client’s full email history and surface the most relevant context inside Dwelly. • Build production NLP / ML-backed backend services that work reliably on messy real-world data. • Improve retrieval and ranking systems using approaches such as RAG, BM25, embeddings, hybrid search and reranking. • Define quality metrics, evaluation datasets and feedback loops for extraction, summarisation and retrieval systems. • Build Python backend services and APIs using frameworks such as FastAPI, Django, Flask or similar. • Integrate ML and LLM workflows into production systems with clear error handling, observability and maintainability. • Work closely with engineering, product and operations teams to turn real business problems into scalable automation systems.

🎯 Requirements

• Strong Python backend engineering experience. • Experience with API frameworks such as FastAPI, Django, Flask or similar. • Production experience with NLP, ML, information extraction, retrieval, ranking or summarisation systems. • Ability to take research ideas or prototypes into production. • Strong understanding of evaluation, metrics and quality measurement for ML / LLM systems. • Practical experience with retrieval systems such as RAG, BM25, embeddings, hybrid search or reranking. • Comfortable working with messy, ambiguous or incomplete real-world data. • Ability to build reliable services around ML workflows, including monitoring, testing and failure handling. • Good understanding of LLM limitations, hallucination risks and safe user-facing AI. • Strong ownership mindset and ability to work independently in ambiguous product areas.

🏖️ Benefits

• Fully remote role. • Competitive compensation based on experience and impact. • Opportunity to work on high-leverage automation systems at the intersection of backend engineering, applied ML, data and real operational workflows. • Competitive salary with the potential for equity options based on performance, recognising exceptional contributions to our integration success.