Staff ML Engineer

Yubo; Paris; Sur place; EUR 80 000 - 110 000; Plein temps

Avantages offerts par ce poste

Equity in the company

Flexible remote work policy

Health insurance coverage for family

Fees for professional events

Résumé du poste

A leading social media platform in Paris is seeking a Staff ML Engineer to enhance its machine learning systems. You'll deliver end-to-end ML use cases, establish standards, and improve lifecycle management of models. The ideal candidate should have 8–10 years of experience in ML, strong expertise in frameworks like PyTorch, and proficiency in Python. Benefits include a competitive salary, flexible remote policy, and comprehensive health insurance.

Qualifications

• 8–10 years of experience in Machine Learning with large-scale datasets.
• Strong expertise in modern ML frameworks like TensorFlow or PyTorch.
• Deep understanding of end-to-end ML systems including deployment and monitoring.

Responsabilités

• Deliver end-to-end ML use cases focusing on safety algorithms.
• Define and improve the full ML lifecycle.
• Contribute to scalable ML development standards across teams.

Connaissances

Machine Learning

Python

Neural networks

LLMs

Data analysis

Production ML systems

Outils

PyTorch

TensorFlow

Description du poste

Who we are

Yubo is the Social Discovery app to make new friends and hang out online. By eliminating likes and follows, we empower our users to create genuine connections and show up as their true selves.

We’ve pioneered a new way for Gen Z to socialize online, and with millions of active users, our goal is to redefine how we connect today and tomorrow.

Our team is international, multicultural and deeply committed to its mission. As the leading platform to socialize online, we have a special responsibility to build a safe digital space for our community. Safety is embedded in our DNA, and our proactive approach focuses on user protection, support, and education. We also work closely with the broader technology industry to share our knowledge and NGOs create industry‑leading child protection standards.

Join us in this exciting journey and help us shape the future of social interactions!

About this role

As Yubo continues to scale, Machine Learning is becoming a core production layer, powering critical systems across safety, recommendations, and product optimization.

What makes this role unique is both the scale and diversity of our data, and the level of maturity we are aiming to reach.

We process massive volumes of images, text, and real‑time user interactions, across millions of users worldwide, creating a wide range of high‑impact ML challenges, including:

• Content moderation (image, text, behavior)

• Recommendation systems and user engagement optimization

• Behavioral detection and trust & safety models

• Emerging use cases such as dynamic pricing and growth optimization

At the same time, our current ML stack is still evolving. Legacy models are not fully integrated into pipelines, lifecycle management remains inconsistent, and our approach can sometimes resemble “develop, deploy, and forget.”

As ML usage expands across the company, this creates increasing complexity and dependency on reliable, well‑structured systems.

There is still a huge amount of untapped potential, with many ML use cases yet to be designed, tested, and scaled, but unlocking it requires building a more robust and scalable ML operating model.

We are therefore looking for a Staff ML Engineer to join our Platform Engineering team, reporting directly to Mikael (Head of Platform Engineering).

Your responsibilities

ML Systems & Delivery

• Deliver end‑to‑end ML use cases (recommendation, safety algorithms, etc.).

• Ensure production readiness, scalability, and long‑term maintainability.

• Balance speed of delivery with robustness and reliability.

ML Lifecycle & Reliability

• Define and improve the full ML lifecycle (training, deployment, monitoring, iteration).

• Establish KPIs and monitoring standards to track model performance over time.

• Ensure continuous alignment with product and safety objectives.

Platform & Standardization

• Contribute to the “ML as a Platform” strategy (tools, workflows, reusable components).

• Define scalable standards for ML development across teams.

• Enable self‑service ML capabilities.

Legacy & Advanced Use Cases

• Take ownership of legacy models and realign them with current business needs.

• Improve, retrain, and integrate them into modern pipelines.

• Define standards for LLM usage (moderation, recommendation).

• Explore and implement advanced ML approaches where relevant.

Cross‑functional Leadership

• Partner with Data Engineering, MLOps, Backend Platform, and Product teams.

• Act as a bridge between ML, platform, and business stakeholders.

• Bring technical leadership and structure to ML practices across the organization.

Our technical environment / ML scope

• ML frameworks: PyTorch

• Languages: Python (data stack)

• Core topics: Neural networks, LLMs, data sampling

• Use cases: Recommendation systems, safety algorithms, moderation

• Ecosystem: Data Engineering, MLOps pipelines, Backend Platform

Who you are

• You have 8–10 years of experience in ML / Data, including work on large‑scale datasets (hundreds of gigabytes).

• You have strong expertise in modern ML frameworks (TensorFlow, PyTorch, JAX).

• You are highly proficient in Python (data ecosystem).

• You have deep knowledge of neural networks and LLMs.

• You understand ML systems end‑to‑end (data → training → deployment → monitoring).

• You have strong experience in production ML systems, not only research.

• You demonstrate strong product sense and can align models with business needs.

• You are pragmatic and impact‑driven (not purely research‑oriented).

• You are able to explain complex ML topics clearly (strong pedagogy).

• You operate well under ambiguity and can structure complex problems.

• You bring technical leadership and influence without authority.

In your first 6 months, you will

• Deliver an end‑to‑end ML use case to validate impact and execution.

• Audit and improve lifecycle management of existing ML models.

• Refactor and retrain at least one legacy safety model.

• Define and implement a reusable OCR standard as a platform component.

• Establish standards for LLM usage in moderation and recommendation systems.

• Contribute to defining the ML platform strategy and operating model.

• Shift the organization from “deploy & forget” to reliable, measurable ML systems at scale.

What we offer

• A highly competitive salary range as well as equity in the company.

• A highly flexible remote work policy, 2 days at the office per month, with monthly team events.

• We also cover fees for external professional events and meetups (Android Makers, etc…).

• Great health insurance coverage for both you and your family by Alan, fully paid for by Yubo !

• Numerous benefits for parents: additional parental leave, easy access to nurseries and daycare facilities in France.

Our approach to privacy & safety

As part of your role, you may handle tools and features involving personal data. We expect all employees to demonstrate strong awareness of privacy and safety issues, and to actively support our Privacy & Safety by Design efforts.

Join Yubo and help shape the future of Social Discovery while enjoying a culture that values flexibility, well‑being, and impact.