ML Ops

Join a leading European dating app as a Senior ML Ops Engineer. You will be responsible for the full lifecycle of ML models in production, working closely with teams in North America and Paris. The position offers a competitive salary, hybrid work model, and opportunities for professional growth.

• Assurer la mise en production des modèles d'apprentissage automatique de bout en bout, y compris l'entraînement, le déploiement, le réentraînement et les retours en arrière.
• Concevoir, maintenir et améliorer les pipelines MLOps, y compris l'intégration continue/déploiement continu (CI/CD), les flux de données et l'orchestration.
• Être responsable de la fiabilité, des performances et de la disponibilité des systèmes d'apprentissage automatique en production.

**👤 Who we’re looking for :**

• **5+ years as ML Engineer / MLOps / Software Engineer** with **strong ML production experience**.
• **Proven track record** putting ML models into production and running them reliably.
• **Solid production mindset:** incidents, SLAs, monitoring, technical debt do not scare you.
• **Strong skills in Python, Docker, CI/CD, Terraform, GCP (Vertex AI, Cloud Run, BigQuery).**
• Comfortable working closely with Data Scientists and platform teams.
• **Very good communication in English;** able to collaborate daily with North American teams.
• Autonomous, rigorous, pragmatic, comfortable as a technical reference without direct reports.

• **Nice to have:** Kafka, Spark, ElasticSearch, Grafana, A/B testing frameworks, BI tools.
• **💰 Package & conditions :**

• **Salary: 70–80 K€ gross per year + ~5% bonus.**
• **Additional:** profit sharing (intéressement and participation) + benefits (lunch vouchers, healthcare, mobility, fitness, etc.).
• **Contract:** full-time permanent position.
• **Location:** Paris
• **Remote:** 2 days remote / week

**🧪 Why this role is attractive :**

• **High-impact ML**: work on matching, coaching, trust & safety, business scoring for millions of users.
• **Modern stack:** GCP, Vertex AI, Cloud Run, BigQuery, Terraform, Grafana; low legacy.
• International culture: daily collaboration with Canada and US, multi-brand environment.
• **Strong learning environment:** e-learning, conferences, knowledge-sharing, hackathons.

• **🧪 Hiring process :**
• **Step 1** – Recruiter screen (video, 30–45 min): career path, motivations, compensation, logistics.
• **Step 2** – Hiring Manager interview (video, 45 min): role understanding, collaboration, communication.
• **Step 3** – Technical interview (video, 60 min): Python coding (algorithms, basic data processing) + technical Q&A with Data Scientists.
• **Step 4** – Technical deep-dive (video, 90 min, full English): live TensorFlow exercises and discussion with a senior ML engineer.
• **Step 5** – Final interview (preferably on-site, 60 min): meeting with Engineering leadership and People team