Senior SWE, ML Engineer – Identity & Audience

🕒 July 21

🇫🇷 France – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Vibe.co

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

📣 Marketing

🛍️ eCommerce

📱 Media

Marketing • eCommerce • Media

Vibe. co is a technology platform that simplifies TV advertising for businesses. It allows brands to easily create and manage their advertising campaigns on major streaming apps and TV channels within minutes. With features like real-time reporting, performance measurement, and targeted audience reach, Vibe. co aims to streamline the advertising process and enhance campaign effectiveness for over 1,000 brands.

📋 Description

• Design and operate the pipelines that give Vibe a coherent view of users across every data source. • Own and improve the clustering algorithm that turns raw events into coherent entities like users and households. • Anticipate scaling pain before it becomes an incident, as log volumes and advertiser usage keep growing. • Run projects end-to-end, from stakeholder requirements through design, implementation, and post-launch iteration. • Build platform-level identity-resolution tooling so every team can resolve identity for the events they own. • Choose architectures that scale economically and quantify the cost impact of those choices. • Shape and execute the roadmap for Vibe's identity stack. • Surface tradeoffs, risks, and decisions to stakeholders without burying them in implementation detail. • Translate ambiguous requests from Product, Sales, ML, and Finance into concrete deliverables.

🎯 Requirements

• 5+ years of experience as an ML engineer building and operating production services. • Hands-on experience with a modern orchestrator (e.g. Dagster), distributed compute (e.g. Spark), and large-scale storage (e.g. Iceberg). • A track record of managing performance and cost at scale with genuinely large datasets. • Demonstrated ability to adapt technical communication to different audiences and align stakeholders with conflicting priorities. • A bias toward shipping value, with judgment about when to build abstractions and when to keep things simple. • Experience running systems in production, not just prototyping them.

🏖️ Benefits

• Variable pay — based on objectives you hit. No arbitrary targets. • Hybrid flexibility — We're in the Heart of Paris and our team is in 3x a week! • Health insurance — Full coverage via Alan. • Meal vouchers — Via Swile. • Annual offsite — The whole team, once a year, somewhere worth the trip. • Tech Syncs — Engineering and Product meet in person at least quarterly, worldwide.