Spotify
Multilingual AI Quality Specialist

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The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.
The Multilingual AI Data Quality space is part of Spotify's Global Language Quality Program within Localization. Bringing together multilingual language quality evaluation and AI data quality, the team helps ensure our AI-powered experiences are accurate, culturally relevant, and trustworthy across languages and markets.
Working closely with Product, Engineering, Data Science, Research, Personalization, Localization, vendors, and market experts, the team develops evaluation methodologies, high-quality datasets, and quality signals that help improve AI experiences and inform product decisions at scale.
What You'll Do:
- Define quality frameworks, evaluation rubrics, thresholds, and methodologies for multilingual AI experiences.
- Design and execute structured evaluations for AI-generated, AI-translated, AI-curated, and recommendation-driven experiences.
- Lead multilingual dataset curation, annotation, enrichment, and ground-truth creation to support AI model development and evaluation.
- Analyze evaluation results, identify quality gaps, and provide actionable recommendations to improve multilingual AI quality.
- Support LLM-as-a-judge workflows, evaluator calibration, and human-AI agreement studies.
- Partner closely with Product, Engineering, Data Science, Research, Localization, vendors, and market experts to improve AI quality signals and inform launch decisions.
- Document best practices and help define quality standards across languages, markets, and AI use cases.
- Contribute to building scalable evaluation capabilities that support the next generation of AI-powered experiences across Spotify.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Who You Are:
- You have experience in multilingual quality evaluation, localization, data curation, annotation, AI evaluation, or related fields, including text-to-text and text-to-speech experiences.
- You understand language quality, cultural relevance, content quality, and user experience across multiple languages and markets.
- You have experience designing or conducting structured evaluations using quality rubrics, audits, annotation projects, or review methodologies.
- You are comfortable using qualitative and quantitative data to identify trends, measure quality, and make recommendations.
- You are familiar with large language models (LLMs), generative AI evaluation, human-in-the-loop workflows, or LLM-as-a-judge methodologies.
- You enjoy working through ambiguity and turning complex quality challenges into practical evaluation strategies.
- You communicate effectively and thrive in highly cross-functional environments, collaborating with technical and non-technical partners alike.
- Experience with recommendation systems, personalization, search, ranking, machine translation, generative AI, dataset creation, annotation operations, evaluator calibration, prompt testing, model evaluation, SQL, Python, dashboards, or annotation platforms is a plus.


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Where You'll Be:
This role is based in London or Stockholm. We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
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