Title : Research Development Software Engineer

Location: London, UK- 50 % on site

End date: 30th June 26 (12 months intent)

Location: A minimum of 50% per week is expected onsite rising to 60% at some point in the future.

Laptop: Microsoft to provide

Role Summary

The successful candidate will own day-to-day technical work spanning research platform development, evaluation pipelines, human-study support, data readiness for downstream research and development, and the effective use of agentic coding workflows to improve research quality and pace. The role is central to maintaining momentum through the next phase of the project, ensuring that community input can be collected, evaluated, processed, and incorporated into the wider ML research and engineering pipeline while working closely with researchers, engineers, and community partners in an inclusive, multidisciplinary environment.

Key Responsibilities

• Lead development and maintenance of the Community Library Creator research platform, including new experimental API and UI features in technologies such as FastAPI and React that support human-AI feedback and synthetic-data workflows for community partners.
• Maintain and extend model evaluation pipelines, including quantitative measures such as FVD and VBench, qualitative workflows, and quality tracking across human studies and platform outputs.
• Develop tools for data generation and analysis to support the exploration and measurement of model capabilities and to support user testing and studies.
• Support community deployments for current NGO cohorts, including evaluation task generation, research platform readiness, and issue triage.
• Manage data ingestion, post-engagement processing, and research-ready data handoff for downstream analysis, evaluation and model development.
• Apply and strengthen agentic coding workflows and modern AI tooling to improve research velocity, code quality, and codebase stewardship.
• Maintain engineering quality and security posture by addressing compliance and vulnerability issues and upholding testing, type checking, and linting practices.

Qualifications and Experience

Required:

• Strong software engineering skills in Python, with experience building maintainable, well-tested, and secure software for evaluation workflows, data pipelines, or experimental platforms, together with strong engineering hygiene and quality practices.
• Strong analytical and problem-solving skills for ambiguous research and engineering challenges, including the ability to work with uncertainty and ambiguity, translate evolving research goals into practical technical solutions, and design robust tools for evaluation, data analysis, and user studies.
• Experience with machine learning experimentation, model evaluation, active learning, human studies, or human-in-the-loop AI systems.
• Experience with FastAPI, React, cloud infrastructure, Azure-hosted services, containers, or data pipelines.