Staff or Senior Machine Learning Engineer - Identity & Audience

Vibe; Paris (TX); Hybrid; USD 110,000 - 191,000; Full time

Benefits offered by this job

Equity

Variable pay

Hybrid flexibility

Health insurance

Meal vouchers

Annual offsite

Tech syncs

Job summary

Vibe is building an Audience First Streaming TV Advertising platform and seeks an experienced ML engineer/data scientist to own identity resolution at scale. You’ll work on turning billions of events into coherent entities for targeting, measurement, and model training, reporting to the Head of Data Platform.

You’ll influence the identity stack roadmap and collaborate across ML, Product, Sales, and Finance.

Qualifications

• 5+ years of experience as an ML engineer or data scientist building and operating production services.
• Experience operating at data scale, using tools like Dagster, Spark, or Iceberg.
• Familiarity with MLOps tooling and practices.
• A track record of leading technical projects end-to-end, from ambiguous requirements to shipped systems.
• Strong cross-functional communication skills, including adjusting detail level for your audience and pushing back constructively

Responsibilities

• Research and build algorithms that resolve coherent entities, like users and households, from billions of events
• Turn machine learning, clustering, and statistical approaches into scalable, production-ready systems
• Lead projects end-to-end, from stakeholder requirements through research, implementation, and post-launch iteration
• Build platform-level identity-resolution tooling so every team can resolve identity behind their own events
• Design for scale from the start; treat unscalable local tests as unfinished work
• Help shape and execute the roadmap for the company'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
• Collaborate with other ML engineers on MLOps problems

Skills

ML Engineer

Data Scientist

Cross-functional comms

MLOps

Production systems

Tools

Dagster

Spark

Iceberg

Job description

Streaming TV is no longer just a brand awareness channel. It’s becoming a core part of the performance marketing mix, alongside search and social. the company.co is building the platform that makes TV work like the rest of the acquisition stack: targeted, measurable, and optimized for results.

the company.co is an Audience First Streaming TV Advertising platform that gives marketers the tools to reach the right audiences, optimize campaigns in real time, and understand what’s actually driving business outcomes. With hyper-targeted segmentation, AI-powered recommendations, real-time optimization, and incrementality measurement, the company brings the precision and accountability of digital advertising to the biggest screen in the house.

Today, more than 12,000 brands use the company.co to reach 120 million+ households. And in August 2026, the company.co became a Walmart company, opening up a new chapter for the business and the industry. With Walmart’s first-party data and purchase signals now part of the the company platform, advertisers can connect TV advertising to real-world transactions and measure the impact of CTV with a level of precision previously associated with platforms like Google and Meta.

This is a unique moment to join the company. With Walmart’s scale, data, and reach behind us, we’re building the next generation of TV advertising and creating a more measurable, performance-driven future for the channel.

About the Role

Data isn't a support function at the company, it's the fuel. Every decision about which ad reaches which household, and when, runs on it. You'll join the Data Platform team and specialize in identity, turning billions of raw events into coherent, usable entities that power targeting, measurement, and the training sets the company's models learn from. You'll report to the Head of Data Platform. This role exists because identity resolution at the company's scale is a hard, unsolved problem, and the team needs someone who can build models that catch the right signal across petabytes of events. You'll get direct, measurable impact: your work decides which ad reaches whom and whether it worked, not a metric buried in a research paper. You'll shape the roadmap for a system every team at the company depends on, and work on a problem that only gets more interesting as CTV scales.

What You'll Do

• Research and build algorithms that resolve coherent entities, like users and households, from billions of events
• Turn machine learning, clustering, and statistical approaches into scalable, production-ready systems
• Lead projects end-to-end, from stakeholder requirements through research, implementation, and post-launch iteration
• Build platform-level identity-resolution tooling so every team can resolve identity behind their own events
• Design for scale from the start; treat unscalable local tests as unfinished work

Cross-Team Partnership

• Help shape and execute the roadmap for the company'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
• Collaborate with other ML engineers on MLOps problems

What You Need

• 5+ years of experience as an ML engineer or data scientist building and operating production services
• Experience operating at data scale, using tools like Dagster, Spark, or Iceberg
• Familiarity with MLOps tooling and practices
  • A track record of leading technical projects end-to-end, from ambiguous requirements to shipped systems
  • Strong cross-functional communication skills, including adjusting detail level for your audience and pushing back constructively
  • Judgment about when to invest in abstraction and when to keep things simple

  Nice to Haves

  • Experience in streaming TV advertising or programmatic advertising

  Our Values

  At the company, we run on three values: Impact, Ambition, and Urgency. We tie every goal to a real business outcome, think 10x rather than settling for good enough, and move daily rather than waiting for perfect conditions.

  You'll thrive here if you own outcomes without needing direction, default to action, and hold yourself to results, not effort.

  This is a high-performance environment with high-performance rewards: you'll work alongside people who push you, with real ownership over hard problems in a market that's moving fast.

  If that sounds like the best version of your career, we want to meet you.

  What We Offer

  The pay range for this role is €99,000 - €171,000. We will support relocation to Paris for great candidates.

  • Equity — Employee Stock Ownership Plan. You're building this; you should own part of it.
  • Variable pay — Based on real the company business goals.
  • 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.

  Our Interview Process

  We respect your time. Here's exactly what to expect — no surprises, no ghosting.

  • Recruiter screen — 30 min. We'll share context; you'll share yours.
  • Manager interview — Meet the person you'd work with directly.
  • Technical Interview — A real problem, not a trick. We'll work through it together.
  • Calibration interview — A senior leader joins to ensure we're holding a consistent, high bar.
  • Offer — Fast. We don't let good decisions sit.
  • Reference checks — Two calls, handled with discretion.

  Equal Opportunity

  Vibe is an equal opportunity employer. We evaluate all applicants without regard to race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.

  We believe the best ideas come from teams with different backgrounds, perspectives, and experiences. If you need a reasonable accommodation during the application or interview process, please let us know.