ML Ops

70–80 K€ gross per year + ~5% bonus + profit sharingParis (hybrid, 3 days on-site / week)Remote: 2 days / week after onboardingEnglish: fluent / French: nice to have5+ years in ML Engineering / MLOps / Software Engineering with strong ML in productionJoin a European Dating App leader where data and ML are at the heart of the product. As a Senior ML Ops Engineer, you will be the reference MLOps engineer in Paris, working hand‑in‑hand with a senior MLOps / ML Engineering team in North America and a Data Science team in Paris.

You will own the full lifecycle of ML models in production on a modern GCP stack, from training pipelines to monitoring and incident handling.

What you will do

• Put ML models into production end to end: training, deployment, retraining, rollbacks.
• Design, maintain and improve MLOps pipelines (CI/CD, data flows, orchestration).
• Own reliability, performance and availability of ML systems in production.
• Implement and operate monitoring, logging and alerting for all ML services.
• Handle production incidents related to ML models and drive post-mortems.
• Support Data Scientists to industrialize their models and experiments.
• Share best practices and help shape the ML architecture and standards.
• Act as the bridge between the Data Science team in Paris and the MLOps / platform team in North America.

Stack & environment

• Language: Python.
• Cloud: GCP (BigQuery, Cloud Run, IAM, service accounts).
• ML services: Vertex AI (training, endpoints, pipelines).
• Deployment: containerized services on Cloud Run, Vertex AI Endpoints.
• CI/CD: automated pipelines, GitHub-based workflows.
• IaC: Terraform for GCP infrastructure.
• Monitoring & observability: metrics, logs, alerts, Grafana.
• Data: BigQuery, event-driven components with Kafka, some legacy Spark/Scala (being phased out).
• Organisation: centralized Data Hub (Data Science, ML/Data Engineering, BI, DBAs), international teams across Europe, Canada and US.

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.