Flexible ML Engineer — Production LLM & RAG Pipelines

WyserAI; United Kingdom; On-site; GBP 70,000 - 110,000; Full time

Job summary

Wyser is seeking a skilled Machine Learning Engineer to help ready and support models from inception to production. You will design, deploy and maintain AI systems across the lifecycle, focusing on LLM pipelines, RAG, and integrated AI services in a regulated environment.

Join a fast-paced, innovative team in the UK, working with Azure-based infrastructure, Gemini and other AI providers. The role emphasizes collaboration with product, engineering and data science to deliver robust ML behavior.

Qualifications

• Minimum 2 years in R&D or product engineering shipping ML/AI features to production.
• Strong Python experience building production services (FastAPI, async, pytest).
• Hands-on LLM application engineering with Gemini or similar providers.
• Experience with RAG or document intelligence systems.
• Solid understanding of Azure cloud services (Blob Storage, Service Bus, Container Apps).
• Comfortable with Git, Docker and collaborative product engineering.
• Experience with vector databases such as QDrant.

Responsibilities

• Design, implement and improve LLM pipelines for speech-to-text, summarisation, extraction, classification and retrieval.
• Build and tune hybrid RAG systems over documents and transcripts.
• Integrate third-party AI services, including Gemini and Azure AI tools, with multi-tenant config.
• Own evaluation loops: regression tests, STT benchmarking, feedback triage, release gates.
• Collaborate with product, engineering and data science to translate domain requirements into ML behavior.

Skills

Python

LLM pipelines

RAG systems

Azure Cloud

Git

Docker

Vector databases

Tools

FastAPI

pytest

Gemini

Azure Document Intelligence

QDrant

Google Gemini Agent Enterprise Platform

Terraform

SQL Server

PostgreSQL

Job description

Wyser is seeking a skilled Machine Learning Engineer to help ready and support models from inception to production. You will design, deploy and maintain AI systems across the lifecycle, focusing on LLM pipelines, RAG, and integrated AI services in a regulated environment.

Join a fast-paced, innovative team in the UK, working with Azure-based infrastructure, Gemini and other AI providers. The role emphasizes collaboration with product, engineering and data science to deliver robust ML behavior.