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ML Ops

About

Chez Bluecoders, nous sommes convaincus que ce ne sont pas les idées qui transforment le monde, mais ceux qui savent les coder.

Depuis 2016, nous accompagnons les startups et scale-ups dans la structuration de leurs équipes techniques, en identifiant les profils tech capables d’avoir un vrai impact.

Recruter dans la tech, c’est notre spécialité. Mais surtout, c’est notre passion. Comprendre une stack, un produit, décoder les signaux faibles, c’est ce qui nous anime chaque jour.

Derrière chaque besoin client, nous cherchons à identifier les vrais enjeux. Ce sont ces échanges en profondeur qui nous permettent de bâtir des process de recrutement rigoureux, sur-mesure, capables d’attirer des profils exigeants.

Notre force: une communauté soudée de recruteurs freelances, tous expérimentés et passionnés. Ensemble, nous partageons une même exigence de qualité et le goût du travail bien fait.

Chez Bluecoders, nous croyons qu’un bon recrutement ne repose pas uniquement sur les compétences. Il repose sur l’alignement entre un projet et une équipe.

Nous savons que c’est de là que naissent les collaborations durables.

Job Description

💰 70–80 K€ gross per year + ~5% bonus + profit sharing

📍 Paris (hybrid, 3 days on-site / week)

🏠 Remote: 2 days / week after onboarding

🌍 English: fluent / French: nice to have

💪 5+ years in ML Engineering / MLOps / Software Engineering with strong ML in production

 

Join a European Dating App leader where data and ML are at the heart of the product. As an 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.

Preferred Experience

👤 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

Additional Information

  • Contract Type: Full-Time
  • Location: Paris
  • Experience: < 6 months
  • Possible partial remote
  • Salary: between 69000€ and 79000€ / year
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