Wiremind

Data Engineer – MLOps

Wiremind

full-time

Posted on:

Location Type: Hybrid

Location: Paris • France

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Tech Stack

Python

About the role

  • At Wiremind, the Data Science team is responsible for the development, monitoring and evolution of all ML-powered forecasting and optimization algorithms used in our Revenue Management systems.
  • You will join a cross-functional team built to be an autonomous department (DevOps, software and data engineering, data science, AI/ML, operations research) and work on a modern MLOps stack composed of Druid (data warehouse), Argo Workflows (pipeline orchestrator), MLflow (models & experiments tracking) and in-house Python packages that glue these components together.
  • As an MLOps Engineer, you will be responsible for:
  • Maintaining the existing MLOps platform used by our ML engineers to train and deploy models
  • Enhancing the MLOps platform with new features such as automated model retraining
  • Deploying ML models to production in a safe, scalable and maintainable way
  • Collaborating daily with our ML team to exchange ideas for improving our solution and to provide technical support for the stack
  • Addressing technical debt, proposing new solutions and challenging architectural decisions to continuously improve the codebase

Requirements

  • Engineering degree with 3 to 5 years of experience in MLOps, software engineering, data engineering or a related field
  • Proficient in a backend programming language and experienced collaborating on large codebases
  • Rigorous and committed to delivering high-quality, well-tested code
  • Interested in data science and ML applications and familiar with the ML project lifecycle
  • Strong troubleshooting skills across multiple layers of architecture
  • Fluent in French and English
Benefits
  • Self-funded startup with a strong technical identity
  • Spacious 700 m² offices in the heart of Paris (Boulevard Poissonnière)
  • Competitive compensation linked to performance
  • A caring, stimulating team that encourages skills development through initiative and autonomy
  • A learning environment with opportunities for career growth
  • Training available on demand
  • Hybrid working policy: 2 remote days per week and the possibility to work occasionally from abroad
  • Strong company culture (monthly afterworks, regular tech and product talks, annual off-site seminars, team-building events…)
  • Annual budget for your IT equipment
  • Partnership with the People & Baby network of inter-company nurseries to support childcare for children aged 0–3
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
MLOpsPythonMLflowDruidArgo Workflowsmodel retrainingdata engineeringsoftware engineeringML applicationstroubleshooting
Soft Skills
collaborationcommitment to qualityproblem-solvingcommunicationrigor
Certifications
engineering degree