AI Research Intern

Salary

Core Qualifications

Preferred Qualifications

Key Responsibilities

• •Take ownership of a focused research question on the Bynder Labs roadmap and drive it from literature review and prototyping through to evaluated experiments
• •Build prototypes and experiments using modern AI tooling, large language models on AWS Bedrock, embedding models, vector search on OpenSearch, agent orchestration frameworks, and the Model Context Protocol (MCP).
• •Design rigorous evaluations for non-deterministic AI systems, including offline benchmarks, LLM-as-a-judge pipelines, and online experiments on real data.
• •Stay up to date with recent research, summarise them for the team, and decide which ideas are worth implementing.
• •Contribute clean, well-tested Python code to shared Labs repositories and follow the engineering practices used by the rest of Bynder R&D.
• •Use our observability stack to understand how AI systems behave in production and propose improvements when they don't behave well.
• •Communicate clearly: write up findings in concise documents, present results at Labs reviews, and translate technical work into language non-technical stakeholders can act on.
• •Be proactive and propose improvements to your project, to our internal tooling, to the way we run experiments.
• •Collaborate with engineers and product managers from other Bynder squads to ship work that lands.