ABOUT VIDSY

Vidsy is a multi-award-winning startup with hubs in London (HQ), NYC, LA, and Toronto. We’re building the ultimate platform for brands and Creators to team up and thrive together. Our platform empowers global brands to produce impactful video ads while giving Creators the tools, opportunities, and fair pay to work on amazing projects. We’re building a different way to create; democratising creativity and empowering brands and Creators to build value together.

ABOUT THE ROLE

As an AI Engineer, you’ll use Generative AI to enhance operations, power client-facing products, and strengthen our data-driven culture.
Owning the full AI lifecycle, you’ll take ideas from proof of concept to deployment and continuous evaluation. Our AI initiatives span categorization, summarization, data analysis, automated content generation, and rich media analysis -leveraging both existing AI/ML tools (LLMs, RAG, embeddings, agentic workflows) and custom solutions.
You’ll collaborate across teams to build practical, scalable AI solutions - where precision matters. With a “you build it, you run it” mindset, you’ll stay hands-on throughout development. We’re looking for an AI-first engineer who drives real value with LLMs and brings bold ideas to life.

RESPONSIBILITIES

• Identify and showcase high-impact AI opportunities, developing proof of concepts to validate feasibility and demonstrate real-world value.
• Explore, collect, clean, and prepare datasets for prompt engineering, model training and evaluation (Data Engineering).
• Design and create robust data pipelines (Data Engineering).
• Develop, test and iterate prompts to optimise performance across relevance, accuracy, consistency and other areas (Prompt Engineering).
• Select, train, and fine-tune AI models based on need, leveraging appropriate techniques (e.g. LLMs, Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, Multi-modal AI, Agentic Workflows) (Model Development).
• Integrate and deploy scalable AI based applications, backend services and APIs (Deployment).
• Develop automated mechanisms and tools for continuous evaluation, benchmarking and optimising of AI solutions, prompts, and models (Eval).
• Improve AI solutions and enhance real-world applicability through qualitative user feedback (Eval).
• Ensure that all AI solutions and tools align with organisational policies, security protocols, and relevant regulations (Compliance).
• Stay up to date with the latest AI advancements and best practices, and drive AI culture empowering your colleagues to apply AI to their own projects.