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Senior Engineer (remote, Europe)🌐 Remote💼 Full-time🗓 2026-06-25

Core

Design, build, and optimize large-scale data products and search systems for creator discovery, including indexing billions of media files and deploying ML models for semantic/vector search.

Role type

Senior IC search and data infrastructure engineer

Builds

Production-ready search engines, indexing pipelines, and recommendation systems for creator economy platforms

Domain

Creator economy, data search, large-scale distributed systems, machine learning

Deliverable

production ML models | product features | infrastructure

Required skills

Large-scale data product design, search system optimization, ML model deployment, vector database management, distributed data processing, system scalability, end-to-end project ownership

Preferred skills

Experience with multimodal embeddings, LLM integration, real-time data pipelines

Technologies

AWS, GCP, Pulumi, Python, TypeScript, Node.js, PySpark, Airflow, ElasticSearch, Milvus, Apache Iceberg, SageMaker, DynamoDB, S3, Glue, Kinesis, Lambda, ECS, Aurora

Responsibilities

Design and build large-scale data products tied to search systems, generate embeddings from images/videos/text/audio at massive scale, create systems for advanced filtering and ranking, deploy ML models for semantic and vector search, design indexing and querying pipelines for low latency, experiment with LLMs and vector databases to enhance search

Seniority

Senior, hands-on IC

Rewrite
## About the role Modash gives brands the tools to work with the right content creators and helps creators earn a living doing what they love. Behind the scenes, we're building the world-class data platform that powers creator discovery for thousands of companies — and we're looking for a hardened Senior Engineer to shape the direction of the creator economy. ## Responsibilities We're not a service function — Data Search & Data Insights are core product capabilities at Modash, building products for customers to use. Data Search is a specialised team in Data Org, and you'll own high impact projects end-to-end, from idea to launch. Here's a typical day: - Start your day with a short standup - Heads-down focus time to design, build, and optimise large-scale data products tied to search systems - Minimal meetings — maximum ownership - Collaborating with data core, data insights, and other product teams to deliver impactful features - Continuously improving search accuracy, speed, and scalability You'll be working on big, impactful projects like: - Building a creator search engine indexing 400M+ influencer profiles and billions of media files - Generating embeddings from images, videos, text, and audio at massive scale - Creating systems for advanced filtering, ranking, and relevance scoring - Deploying the latest ML models for semantic and vector search into production within weeks - Designing indexing and querying pipelines to serve millions of requests with low latency - Experimenting with how LLMs, multimodal embeddings, and vector databases can enhance search & recommendations You won't be patching pipelines — you'll be creating production-ready search products from scratch that directly impact customers. ## The Data Team At Modash, search is a joint effort within the Data Team. You'll work closely with tightly aligned teams, including: - Data Core – building large-scale raw data collection systems that power every internal and customer-facing product. - Data Insights – building and operating the social media data products customers rely on, ensuring reliable, fresh, high-quality access and a trusted intelligence layer We value autonomy, but we also love to work closely as a team — through pair programming, reviews, and shared wins. You'll collaborate with the CEO, CTO, engineers, sales, and even customers to shape what we build. Everyone takes ownership, but nobody works in isolation. We're remote-first, but we connect IRL at regular team offsites to collaborate, reflect, and have fun. ## Our tech stack - AWS and GCP with Pulumi (IaC) - Python, Typescript and Node.js - PySpark on AWS EMR for data processing - Airflow for orchestration - ElasticSearch - Milvus Vector DB (Zilliz) - LLM Batch APIs - Apache Iceberg - SageMaker, DynamoDB, S3, Glue, Kinesis, Lambda, ECS, Aurora - Tools: Slack, GitHub, Linear, Notion, Cursor ## The interview process We move fast. You can get interviewed in under a week. Process consists of: - Intro chat - Coding
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