Operations Specialist, AI Enablement [Content Moderation]
Bumble Inc. UK LondonEst. Est. GBP 45,000–65,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Agile
Introduction to Role & Team
Bumble Inc. is looking for an Operations Specialist, AI Enablement to join our CX & Trust team. Trust, care, and high-quality experiences are central to Bumble’s mission to create a world where all relationships are healthy and equitable, and in this role you’ll help bring that mission to life by improving how our AI-powered customer experience and moderation systems support our community.
You’ll evaluate AI-powered customer interactions and automated moderation decisions against Bumble’s policies, processes, and quality standards, helping us understand where our systems are performing well and where they can improve. Through quality reviews, accurate case labelling, golden-set maintenance, and thoughtful analysis, you’ll help ensure AI-supported decisions are consistent, precise, and grounded in the nuance required to serve our members responsibly. You’ll work closely with the AI Performance & Enablement Manager and colleagues across CX & Trust, taking ownership of high-quality work and demonstrating our Bumble values of Courage, Curiosity, Respect, and Excellence as we reimagine how AI can strengthen trust and care across the member experience.
This role will be based in London and will work in a hybrid model.
What you’ll do
Conduct quality reviews of AI-powered customer conversations and automated moderation decisions, assessing their alignment with Bumble’s community policies, operational processes, and quality standards.
Analyse policy enforcement gaps and nuanced cases, identifying where automated decisions may be inconsistent, unclear, or misaligned with policy intent and surfacing actionable insights for improvement.
Perform accurate case labelling to support AI model training, evaluation pipelines, and ongoing quality benchmarking, demonstrating Excellence through careful and consistent application of established guidance.
Review and maintain golden sets that reflect current policy standards and provide reliable ground truth for assessing AI quality, accuracy, and precision.
Report quality issues through established workflows, taking ownership of accurate categorisation, clear documentation, and actionable feedback, and seeing insights through to meaningful impact.
Collaborate purposefully with the AI Performance & Enablement Manager on scoring consistency, calibration, recurring quality issues, and opportunities to strengthen AI reliability and the member experience.
Identify patterns and share learnings that can improve AI accuracy and precision, customer satisfaction, and operational efficiency, approaching emerging challenges with Curiosity and an agile mindset.
Use QA platforms and AI-supported tools, including systems such as Cinder, Zendesk QA, and Bumble’s internal assessment tooling, to monitor quality and understand AI behaviour, reviewing outputs critically for accuracy, bias, privacy, and fairness and applying human judgment before acting on results.
About you
Requires 1+ years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
Bring experience or transferable skills from Trust & Safety, content moderation, Customer Experience, quality assurance, or another fast-paced, policy-driven environment.
Have a sharp eye for detail and can objectively evaluate conversations, moderation decisions, and other interactions against established policies, processes, and quality standards.
Bring familiarity with conversational AI systems, chatbots, automated moderation, or AI-supported workflows, with the Curiosity to continue learning how these systems behave, where their limitations lie, and how human judgment can improve their effectiveness.
Understand, or are motivated to learn, quality assurance practices such as case labelling, calibration, consistent scoring, golden-set evaluation, and clear documentation of quality findings.
Are comfortable learning digital tools and platforms and can use data an
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