Research Engineer - Large-Scale Search & Data Platforms

Mistral; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Mistral in London seeks a Research Engineer to join the newly formed Search and Services Platform. You will build and operate large-scale search infrastructure that our models rely on, from self-hosted indices to knowledge graphs and databases, enabling data generation and training runs.

You will collaborate with researchers and data platform teams to ensure reliability, scalability, and fast performance across extensive storage and compute resources, supporting model development and deployment.

Qualifications

• 5+ years of experience in search engineering or data infrastructure.
• Strong Python and Go programming skills.
• Hands-on with Vespa, Elasticsearch/OpenSearch, or similar systems.
• Experience with large-scale data pipelines and incident response.
• Familiarity with Kubernetes and infra-as-code.

Responsibilities

• Design, build and operate large-scale search infra including Vespa clusters and vendor search endpoints.
• Maintain structured data sources and knowledge graphs (Wikidata, UniProt) and scientific data.
• Design interfaces to expose services to models via queries and MCPs.
• Build data pipelines to ingest, index and serve massive datasets.
• Collaborate with researchers and adjacent teams to enable effective data services.
• Create documentation and guidance to help teams use the services.

Skills

Search engineering

Data infrastructure

Python

Go

Distributed systems

SRE practices

Communication

Autonomy

Tools

Vespa

Elasticsearch

OpenSearch

Kubernetes

PostgreSQL

ClickHouse

Infra-as-code

Job description

Mistral in London seeks a Research Engineer to join the newly formed Search and Services Platform. You will build and operate large-scale search infrastructure that our models rely on, from self-hosted indices to knowledge graphs and databases, enabling data generation and training runs.

You will collaborate with researchers and data platform teams to ensure reliability, scalability, and fast performance across extensive storage and compute resources, supporting model development and deployment.