AI Engineer
At a glance
Mid-level AI Engineering role at MediaRadar. Madrid · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Take ML problems from initial definition through system design and production-ready implementation
- Build classification and attribution models for ad creatives and brand deduplication using registry data
- Create chain-of-thought prompts and agent workflows that handle complex attribution decisions
- Improve vector search, database migrations and ingestion speed, then add monitoring and safeguards
What you bring
- Expert Python skills, including asynchronous programming, typing and performance tuning
- Strong computer science or telecommunications degree, plus deep SQL and vector database knowledge
- Hands-on experience deploying RAG pipelines and LLM agents
Who this fits
This suits an independent software-minded engineer who can take work through to completion without close supervision. The role calls for regular in-person collaboration with the Madrid tech team at a local WeWork.
From the employer
Location: Madrid, Spain (Remote — with regular in-person collaboration at a local WeWork alongside our Madrid tech team)
About MediaRadar
MediaRadar, now including the data and capabilities of Vivvix, powers the mission-critical marketing and sales decisions that drive competitive advantage. Our competitive advertising intelligence platform enables clients to achieve peak performance with always-on data and insights that span the media, creative, and business strategies of five million brands across 30+ media channels. By bringing the advertising past, present, and future into focus, our clients rapidly act on the competitive moves and emerging advertising trends impacting their business.
Job Summary
We are building a best-in-class AI team focused on delivering advanced capabilities that empower our data organization. This is not a role for theoretical research; it is for an AI Engineer with a strong Software Engineering backbone.
You will be expected to be highly independent, taking ownership of problems from end-to-end. We value "Modern Productivity"—you should leverage LLMs and AI coding assistants to bypass boilerplate and ship code faster. In our view, manual line-by-line coding is outdated; we want engineers who use every tool at their disposal to increase output without sacrificing reasoning or quality.
Stack Highlights:
Core: Expert Python (Non-negotiable), PostgreSQL + pgvector, SQLAlchemy.
AI/LLM: Azure OpenAI, LangChain, Langfuse, Multi-agent orchestration.
Productivity: ChatGPT/Copilot for development, Docker, async I/O.
Key Responsibilities
- Independent System Building: Own the design and implementation of scalable ML solutions, moving rapidly from problem statement to working code.
- Classification & Attribution: Build and fine-tune systems for complex data, such as identifying ad creatives or global brand deduplication by cross-referencing government registries.
- Advanced Reasoning: Implement "Chain of Thought" prompting and multi-agent workflows (e.g., classification agents vs. reasoning agents) to solve complex attribution tasks.
- Data Engineering Rigor: Optimize vectorization, manage migrations via Alembic, and ensure high-throughput ingestion with minimal supervision.
- Operational Excellence: Implement guardrails and observability (Langfuse) to ensure that high-velocity output remains explainable and robust.
Requirements
Key Qualifications
- Academic Foundation: Strong degree in Computer Science or Telecommunications (Teleco).
- Software Rigor: You think like a developer. Clean code, architecture, and scalability are your default settings.
- The "Hacker" Spirit: Active participation in Hackathons or a portfolio of ambitious side projects. We want to see that you build things because you love solving problems.
- Extreme Independence: Proven ability to thrive in international roles without constant lead structure or heavy supervision.
- Technical Mastery:
- * Expert Python (typing, async, performance).
- Deep SQL & Vector DB knowledge (pg_trgm, HNSW).
- Experience building and deploying RAG pipelines and LLM agents.
Skill Focus for 2026
- Vision-based ML: Using reasoning to correctly attribute visual ad creatives.
- Context Optimization: Utilizing window context detection to improve system reasoning.
- Multi-Agent Scaling: Chaining specialized models to automate complex data workflows.
Benefits
At MediaRadar, we are committed to creating an inclusive and accessible workplace where everyone can thrive. We believe that diversity of backgrounds, perspectives, and experiences makes us stronger and more innovative. We are proud to be an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other legally protected status.
In accordance with the EEO-1 reporting requirements, we collect demographic data as part of our efforts to ensure fair and equitable hiring practices across all levels of our organization.
We are committed to ensuring our recruitment process is accessible to all applicants. If you need a reasonable accommodation during the application or interview process, please contact us at careers@mediaradar.com .
We’re excited to meet people who share our values and want to build the future with us!