Senior ML Engineer, Identity & Audience (Production)

Vibe; Paris; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Variable pay

Hybrid flexibility — Paris, in-office

Health insurance

Meal vouchers

Annual offsite

Tech Syncs

Job summary

Vibe in Paris is hiring a Senior Machine Learning Engineer for Identity & Audience. You’ll join the Data Platform team to own the identity stack, turning events into targetable identities at US scale and production pace.

Build scalable pipelines, clustering, and tooling to empower Product, Sales, ML, and Finance. The role demands 5+ years of ML experience, hands-on work with Dagster, Spark, and Iceberg, and a strong track record in production systems, performance, and cost management.

Qualifications

• 5+ years of experience as an ML engineer in production.
• Hands-on with Dagster, distributed compute (Spark), and Iceberg.
• Track record of managing performance and cost at scale.
• Able to adapt technical communication to different audiences.
• Bias toward shipping value and pragmatic abstraction decisions.
• Experience running systems in production, not just prototyping.

Responsibilities

• Own and operate the identity stack end-to-end across data sources.
• Improve clustering of events into users/households and scale.
• Anticipate scaling pains and prevent incidents in production.
• Run projects end-to-end from requirements to post-launch iteration.
• Build identity-resolution tooling for other teams.
• Shape and execute the identity stack roadmap with stakeholders.
• Translate requests from Product, Sales, ML, and Finance into deliverables.

Skills

ML engineering

Production readiness

Cross-team communication

Tools

Dagster

Spark

Iceberg

Job description

Vibe in Paris is hiring a Senior Machine Learning Engineer for Identity & Audience. You’ll join the Data Platform team to own the identity stack, turning events into targetable identities at US scale and production pace.

Build scalable pipelines, clustering, and tooling to empower Product, Sales, ML, and Finance. The role demands 5+ years of ML experience, hands-on work with Dagster, Spark, and Iceberg, and a strong track record in production systems, performance, and cost management.