At Dailymotion, we’re building AI-powered products that rely on high-quality, well-governed data—from advertising optimization and measurement to trust & safety and internal decision-making tools.

We are looking for an AI Data Engineer to design and operate the data pipelines, datasets, and evaluation workflows that make our AI systems reliable, reproducible, and measurable in production.

In this role, you’ll work at the intersection of data engineering, ML/LLM product needs, and platform reliability, partnering closely with AI/ML engineers, product engineers, and analytics stakeholders. You’ll help ensure that the data powering training, retrieval (RAG), evaluation, and monitoring is curated, traceable, and secure—so teams can ship AI features with confidence.

We offer challenging work with direct business impact, opportunities to learn and grow, and a collaborative culture that encourages every team member to bring their point of view to the table.

Responsibilities

• Build and maintain reliable data pipelines (batch and/or streaming) that power AI features, evaluation, and analytics use cases.
• Develop curated datasets and feature tables for training and evaluation; implement validation checks, lineage, and clear ownership.
• Support knowledge ingestion for RAG: document processing, chunking, metadata enrichment, indexing/backfills, and freshness monitoring.
• Implement and operate evaluation data workflows: golden sets, labeling support, drift checks, regression reporting, and dataset versioning.
• Collaborate with AI/ML and product engineers to translate requirements into scalable data models and pipelines.
• Improve pipeline performance and cost efficiency through incremental processing, partitioning, and resource tuning on GCP.

Contribute to operational excellence: monitoring, alerting, troubleshooting, and

Dailymotion is proud to be an equal employment opportunity and affirmative action employer. We value inclusion and we want you to help us thrive for a more diverse community.

All our job offers are open to people with disabilities or impairments, and we actively encourage everyone to apply. If you have any accessibility needs or require any accommodations for the hiring process, please let us know in advance so that we can make any necessary arrangements.

• Location: Paris

• Start Date: Asap

• Contract Type: Permanent

🔍Want to learn more about us:

• Dailymotion.com

• New-York office - BuiltIn

• Offices in France - Welcome to the Jungle

• Our articles  

For the France offices :

🏡Hybrid Work Framework, depending especially on the needs of your position, ability to work 3 months abroad

💰 Saving Plan Canal +

🍼  Paternity leave or Coparental leave extended 

🕶️  Living Employee Culture (Events/Trainings/Parties/All hands,…) 

🚀  Career development support (training/internal mobility/compensation cycle/360 feedback review …)

🏥  High-end Health Insurance and Personal Services Vouchers (CESU)

⛱️  Paid Time off – RTT and Saving time plan (CET)

✅  Meal Vouchers – Public Transport and Bike refund 

🎡 European Economic and Social Committee (sport membership/cinemas vouchers/gift vouchers/discount) 

⚽Fitness Subscription thanks to our partnership with Gymlib

Qualifications — Required Skills

• Professional English proficiency is required (written and spoken).
• Solid experience building production data pipelines and data models (ETL/ELT concepts, orchestration, reliability, and data quality).
• Strong SQL skills and practical knowledge of warehouse/lake patterns and debugging data issues.
• Proficiency in Golang and/or Python for data processing and pipeline development (depending on your internal standards).
• Understanding of AI/data needs: reproducibility, dataset versioning, evaluation data management, and secure handling of sensitive data.
• Ability to deliver well-tested, well-documented work (CI for data jobs, unit/integration tests for transforms).

Preferred Skills

• Experience with GCP-native data tooling (e.g., BigQuery, Dataflow, Pub/Sub, GCS—adapt to what you actually use).
• Familiarity with embedding pipelines and indexing operations used for retrieval (backfills, monitoring, freshness SLAs).
• Experience with orchestration tools and data quality frameworks, and setting up meaningful SLAs/alerts for pipelines.
• Good operational habits: on-call readiness, cost awareness, and pragmatic automation.
• Experience using AI-powered developer tools (e.g., ChatGPT, Claude, GitHub Copilot) for coding assistance, debugging, and test generation.