Collective.work

AI engineer in recruitment technology

In short

AI Engineer role at an AI-powered recruitment technology company serving over 20,000 recruiters across France, Belgium, Spain and the wider EMEA market, now expanding into the UK. The role covers building and shipping AI features (sourcing, candidate matching, outreach, job distribution, ATS integrations), improving AI models via experimentation and prompt engineering, and working full-stack across AI and JavaScript stacks including backend services, data pipelines and APIs. Requires around 2 years of experience at a middle level, with a hybrid work setup in London.

About
Collective is building the next generation of AI-powered recruitment technology. Their mission is to help professional recruiters find, engage, and hire the right talent faster. Currently, they support over 20,000 recruiters and headhunters across France, Belgium, Spain, and the wider EMEA market, and are accelerating their expansion into the UK.
Responsibilities
•Build new AI features by designing, developing, and shipping AI-powered capabilities across the suite of agents, including sourcing, candidate matching, outreach, job distribution, and ATS integrations.
•Improve AI models continuously through experimentation, evaluation, prompt engineering, and model optimisation to enhance quality, relevance, and reliability.
•Leverage large-scale professional profile data and active candidate networks to improve search, ranking, matching, and candidate recommendations.
•Build production-grade AI systems by integrating LLMs and other AI technologies into scalable, reliable, and low-latency product experiences.
•Experiment with new models, tools, and techniques, evaluate their real-world impact, and quickly turn promising ideas into features.
•Own the full stack, working across AI and JavaScript stacks, including backend services, data pipelines, APIs, and user-facing product features.
•Define and track quality metrics, build evaluation workflows, and use product feedback and real-world usage to continuously improve AI systems.
Conditions
•Hybrid work model

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