MediaRadar, Inc.
MediaRadar, Inc.
201 – 500 Employees
AdvertisingMarketingSaaS
MediaRadar, Inc. is a marketing and advertising SaaS company that develops advertising intelligence tools for media sellers, advertisers, and agencies. Its platform brings together data on more than 4 million brands and associated contacts, helping teams identify prospects, evaluate advertising activity, plan media investments, support buying decisions, and strengthen sales enablement. MediaRadar applies AI-powered analysis to turn advertising data into practical insights for media mix planning and revenue-focused decision-making across the ad tech ecosystem.

AI Engineer – Madrid Hybrid

Build scalable machine learning, retrieval-augmented generation, and multi-agent systems for MediaRadar’s advertising intelligence platform. Develop attribution models, vector search capabilities, and observable AI workflows.

Description

  • Independently design and deliver scalable machine learning solutions
  • Develop and refine classification and attribution systems for complex datasets, including ad creatives and global brand deduplication
  • Apply chain-of-thought prompting techniques and build multi-agent workflows
  • Improve vectorization performance and handle database migrations with Alembic
  • Maintain high-throughput data ingestion pipelines with limited supervision
  • Add guardrails and Langfuse observability to support explainable, reliable AI outputs
  • Use AI coding tools and large language models to improve engineering productivity

Requirements

  • A strong degree in Computer Science or Telecommunications
  • Expertise in clean code, software architecture, and scalable system design
  • Active hackathon participation or a portfolio of ambitious personal projects
  • Ability to work effectively in international roles with limited supervision and without constant lead support
  • Advanced Python skills, including typing, asynchronous programming, and performance optimization
  • Deep knowledge of SQL and vector databases, including pg_trgm and HNSW
  • Experience building and deploying RAG pipelines and LLM agents
  • Knowledge of vision-based machine learning, window-context detection, and scaling multi-agent systems

Benefits

  • Inclusive and accessible workplace
  • Equal Opportunity Employer
  • Reasonable accommodations available during the application and interview process

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