AI Research Engineer

Years of Experience

3–6 years of experience combining software engineering with applied AI/NLP
research.
Experience in a localization or multilingual AI platform context is a strong
plus.

 Evaluate large language models (GPT family, Claude, open-source
models) for localization tasks — measuring quality, cost, and latency
trade-offs; translate findings into engineering decisions.
 Develop and maintain backend microservices and NLP pipelines in
Python and C# (.NET), shipping research conclusions as production
features.
 Build proof-of-concept implementations to validate new approaches:
model integrations, orchestration patterns (e.g., MCP), caching and
batching strategies.
 Design and run experiments: define evaluation sets and metrics, analyse
results, communicate uncertainty and recommendations to the team.
 Write and execute QA test cases for platform features; maintain test
coverage and report issues with clear reproduction steps.
 Present research findings and PoC results at sprint reviews,
communicating to both technical and non-technical stakeholders.
 Investigate and resolve production issues: concurrency bugs,
performance bottlenecks, LLM integration failures.
 Work with Azure cloud services (App Service, Azure Functions,
Service Bus, CosmosDB) and CI/CD pipelines in Azure DevOps.