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Jobs / Modash

Senior Software Engineer - Data Search (remote, Europe)

Modash·Paris, FranceRemotesenior

In short

  • →Ingeniero senior que mejora el buscador de creadores en una plataforma de 400M perfiles.
  • →Construye sistemas de búsqueda multimodal con embeddings de texto, imagen, video y audio a gran escala.
  • →Trabaja desde la idea hasta la producción, con autonomía real sobre resultados y métricas.

Fluency in English is required for collaboration with global teams.

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The questions they'll ask you

1. ¿Cómo evaluarías el impacto de un nuevo embedding multimodal en la relevancia de los resultados de búsqueda?

2. Describe cómo implementarías una pipeline de embeddings de video a gran escala con control de calidad y latencia.

3. ¿Qué métricas usarías para decidir si un reranker de LLM debe ir a producción, y cómo las medirías en entorno real?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

  • ✓Experiencia comprobada en sistemas de búsqueda a gran escala.
  • ✓Conocimiento profundo en embeddings multimodales (texto, imagen, video, audio).
  • ✓Capacidad para diseñar y operar pipelines de datos de alto rendimiento.
  • ✓Experiencia con LLMs y herramientas de ranker/reranker para búsqueda.
  • ✓Habilidad para evaluar tradeoffs entre costo, latencia y calidad en producción.
  • ✓Experiencia en lanzar funcionalidades de búsqueda desde experimento hasta producción.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonScalaGoPostgreSQLRedisKafkaAirflowAWSDockerGCP

Who should you write to at Modash?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Hey, I'm Adrian . I’m hiring a Senior Software Engineer to join the Data Search team at Modash. Modash helps brands find, understand, and work with creators across Instagram, TikTok, and YouTube. More than 2,700 companies—including Stanley 1913, Sennheiser, and NordVPN—use us to manage and scale their creator partnerships. Behind that product is a fascinating search problem: helping customers find the right people across 400M+ creator profiles and billions of media files. We’re combining large-scale data processing, traditional retrieval, vector search, multimodal embeddings, and LLMs to make that possible. That’s where you come in. Why we're hiring Search at Modash isn't an internal platform or a support function. It is one of the core products customers use to discover creators. The scale is large, the data is messy, and the search intent is often complex. A customer might be looking for creators in a specific niche, people whose content conveys a certain visual style, or accounts that resemble a group they already know. Solving that well requires more than adding another filter or calling an LLM API. We need a senior engineer who can work across the full retrieval system—from data and indexing pipelines to embeddings, ranking, relevance, and low-latency serving—and take ambiguous product problems all the way to production. You’ll join the specialised Data Search team and work closely with Data Core, Data Insights, product teams, customers, and company leadership. You’ll have real autonomy, but you won’t work in isolation. If you want a feel for how we think about building software, check our Engineering Blog . What you'll actually own 1. Make creator search meaningfully better. You’ll improve how customers discover creators across 400M+ profiles and billions of media files. That includes retrieval, filtering, ranking, relevance, speed, and the product decisions that connect them. 2. Turn multimodal data into searchable intelligence. You’ll build systems that generate and use embeddings from images, video, text, and audio at massive scale—then make those signals useful in a real customer-facing search experience. 3. Ship new search capabilities into production. You’ll evaluate models and technologies pragmatically, understand tradeoffs around cost, latency, and quality, and move promising approaches from experiment to a reliable production system within weeks rather than quarters. 4. Own the system end to end. You’ll help shape the problem, gather requirements, design the architecture, write the code, release it, measure the outcome, and improve it. Senior engineers here own results, not just implementation tasks. What the day-to-day looks like Here’s what a typical week might include: Monday. A customer search is returning technically relevant but unhelpful results. You inspect the retrieval and ranking stages, identify where intent is being lost, and propose a measurable improvement. Tuesday. Deep-focus time. You build a pipeline to generate multimodal embeddings across a large batch of creator content and test how the new representation affects retrieval quality and cost. Wednesday. You work with Data Insights on a new in-house datapoint. Together, you agree on its definition, coverage, and data-quality requirements, then expose it in Search to give customers more ways to discover creators. Thursday. You test a reranking model on a fixed set of real customer queries. You measure how much it improves relevance against the latency and inference cost it adds, then decide what's ready for production. Friday. You review production metrics, investigate a relevance regression, and share what you learned with the team. The fix may be in the model, the data, the query logic, or the product itself—you follow the evidence. We keep meetings purposeful and protect time for deep work. You’ll have a short standup, close collaboration when it helps, and plenty of space to design, build, optimise, and launch. Requirements What you've done

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