Staff ML Engineer

Yubo; Paris; Hybride; EUR 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Competitive salary and equity

Flexible remote work policy

Coverage of fees for professional events

Comprehensive health insurance

Résumé du poste

Yubo is seeking a Machine Learning Expert to deliver end-to-end ML solutions, ensuring production readiness and improving ML systems. Candidates need to have 8–10 years of experience in the field and strong proficiency in Python and ML frameworks such as PyTorch. The role offers a highly flexible remote work policy, a competitive salary, equity, and comprehensive health benefits for employees and their families. Join Yubo to shape the future of Social Discovery in a nurturing, impact-driven environment.

Qualifications

• 8–10 years of experience in ML/data with large datasets.
• Expertise in modern ML frameworks like TensorFlow and PyTorch.
• Deep knowledge of neural networks and machine learning lifecycle.

Responsabilités

• Deliver end-to-end ML use cases, such as recommendation systems.
• Ensure production readiness and establish ML monitoring standards.
• Lead cross-functional teams to align ML practices with business needs.

Connaissances

Machine Learning Expertise

Python Proficiency

Neural Networks Knowledge

Effective Communication

Problem Structuring

Outils

PyTorch

TensorFlow

Python

Description du poste

About Yubo

Yubo is the Social Discovery app that makes it easy to meet new friends and hang out online. By eliminating likes and follows, we empower our users to build genuine connections and be their true selves.

About This Role

As Yubo continues to scale, machine learning has become a core production layer, powering critical systems across safety, recommendations, and product optimization. This role uniquely tackles large‑scale diverse data and strives to build a mature, robust ML operating model.

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

• 8–10 years of experience in ML / data, including work on very large datasets.
• Strong expertise in modern ML frameworks (TensorFlow, PyTorch, or JAX).
• Highly proficient in Python and the data ecosystem.
• Deep knowledge of neural networks and LLMs.
• Understand end‑to‑end ML systems (data → training → deployment → monitoring).
• Experience building production ML systems, not just research.
• Strong product sense and ability to align models with business needs.
• Pragmatic and impact‑driven, not purely research‑oriented.
• Effective communicator who can explain complex ML topics clearly.
• Capable of working well under ambiguity and structuring complex problems.
• Technical leader who can 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.
• Help shift the organization from “deploy & forget” to reliable, measurable ML systems at scale.

What We Offer

• Competitive salary and equity in the company.
• Highly flexible remote work policy (two days at the office per month) with monthly team events.
• Coverage of fees for external professional events and meetups.
• Comprehensive health insurance for you and your family.
• Numerous benefits for parents, including additional parental leave and access to nurseries and daycare 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 actively support our Privacy & Safety by Design initiatives.

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